Distributed and Cloud Computing: From Parallel Processing to the Internet of Things | Guide books

Distributed and Cloud Computing: From Parallel Processing to the Internet of ThingsOctober 2011

October 2011

Publisher:

Morgan Kaufmann Publishers Inc.
340 Pine Street, Sixth Floor
San Francisco
CA
United States

ISBN:978-0-12-385880-1

Published:31 October 2011

Pages:

672

PDF eReader ePub

Bibliometrics

Sections

2011

Abstract

From the leading minds in the field, Distributed and Cloud Computing is the first modern, up-to-date distributed systems textbook. Starting with an overview of modern distributed models, the book exposes the design principles, systems architecture, and innovative applications of parallel, distributed, and cloud computing systems. It will teach you how to create high-performance, scalable, reliable systems, providing comprehensive coverage of distributed and cloud computing, including: Facilitating management, debugging, migration, and disaster recovery through virtualization Clustered systems for research or ecommerce applications Designing systems as web services Social networking systems using peer-to-peer computing Principles of cloud computing using examples from open-source and commercial applications Using examples from open-source and commercial vendors, the text describes cloud-based systems for research, e-commerce, social networking and more. Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more Designed to meet the needs of students taking a distributed systems course, each chapter includes exercises and further reading, with lecture slides and solutions available online

References

Amazon EC2 and S3, Elastic Compute Cloud (EC2) and Simple Scalable Storage (S3). http://en .wikipedia.org/wiki/Amazon_Elastic_Compute_Cloud and http://spatten_presentations.s3.amazonaws .com/s3-on-rails.pdf.Google Scholar
M. Baker, R. Buyya, Cluster computing at a glance, in: R. Buyya (Ed.), High-Performance Cluster Computing, Architecture and Systems, vol. 1, Prentice-Hall, Upper Saddle River, NJ, 1999, pp. 3-47, Chapter 1.Google Scholar
A. Barak, A. Shiloh, The MOSIX Management System for Linux Clusters, Multi-Clusters, CPU Clusters, and Clouds, White paper. www.MOSIX.org//txt_pub.html, 2010.Google Scholar
L. Barroso, U. Holzle, The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines, Morgan & Claypool Publishers, 2009. Google ScholarCross Ref
G. Bell, J. Gray, A. Szalay, Petascale computational systems: balanced cyberstructure in a data-centric World, IEEE Comput. Mag. (2006). Google Scholar
F. Berman, G. Fox, T. Hey (Eds.), Grid Computing, Wiley, 2003.Google Scholar
M. Bever, et al., Distributed systems, OSF DCE, and beyond, in: A. Schill (Ed.), DCE-The OSF Distributed Computing Environment, Springer-Verlag, 1993, pp. 1-20. Google Scholar
K. Birman, Reliable Distributed Systems: Technologies, Web Services, and Applications, Springer-Verlag, 2005. Google ScholarDigital Library
G. Boss, et al., Cloud Computing-The BlueCloud Project. www.ibm.com/developerworks/websphere/zones/hipods/, October 2007.Google Scholar
R. Buyya (Ed.), High-Performance Cluster Computing, Vol. 1 and 2, Prentice-Hall, Englewood Cliffs, NJ, 1999.Google Scholar
R. Buyya, J. Broberg, A. Goscinski (Eds.), Cloud Computing: Principles and Paradigms, Wiley, 2011. Google Scholar
T. Chou, Introduction to Cloud Computing: Business and Technology. Lecture Notes at Stanford University and Tsinghua University, Active Book Press, 2010.Google Scholar
G. Coulouris, J. Dollimore, T. Kindberg, Distributed Systems: Concepts and Design, Wesley, 2005. Google Scholar
D. Culler, J. Singh, A. Gupta, Parallel Computer Architecture, Kaufmann Publishers, 1999.Google Scholar
B. Dally, GPU Computing to Exascale and Beyond, Keynote Address at ACM Supercomputing Conference, November 2010.Google Scholar
J. Dean, S. Ghemawat, MapReduce: Simplified Data Processing on Large Clusters, in: Proceedings of OSDI 2004. Also, Communication of ACM, Vol. 51, 2008, pp. 107-113. Google Scholar
J. Dongarra, et al. (Eds.), Source Book of Parallel Computing, Morgan Kaufmann, San Francisco, 2003. Google Scholar
I. Foster, Y. Zhao, J. Raicu, S. Lu, Cloud Computing and Grid Computing 360-Degree Compared, Grid Computing Environments Workshop, 12-16 November 2008.Google Scholar
D. Gannon, The Client+Cloud: Changing the Paradigm for Scientific Research, Keynote Address, IEEE CloudCom2010, Indianapolis, 2 November 2010.Google Scholar
V.K. Garg, Elements of Distributed Computing. Wiley-IEEE Press, 2002. Google Scholar
R. Ge, X. Feng, K. Cameron, Performance Constrained Distributed DVS Scheduling for Scientific Applications on Power-aware Clusters, in: Proceedings Supercomputing Conf., Washington, DC, 2005. Google Scholar
S. Ghosh, Distributed Systems-An Algorithmic Approach, Chapman & Hall/CRC, 2007. Google Scholar
B. He, W. Fang, Q. Luo, N. Govindaraju, T. Wang, Mars: A MapReduce Framework on Graphics Processor, ACM PACT'08, Toronto, Canada, 25-29 October 2008. Google Scholar
J. Hennessy, D. Patterson, Computer Architecture: A Quantitative Approach, Morgan Kaufmann, 2007. Google Scholar
T. Hey, et al., The Fourth Paradigm: Data-Intensive Scientific Discovery, Microsoft Research, 2009.Google Scholar
M.D. Hill, et al., The Data Center as a Computer, Morgan & Claypool Publishers, 2009.Google Scholar
K. Hwang, Advanced Computer Architecture: Parallelism, Scalability, Programming, McGraw-Hill, 1993. Google Scholar
K. Hwang, Z. Xu, Scalable Parallel Computing, McGraw-Hill, 1998. Google Scholar
K. Hwang, S. Kulkarni, Y. Hu, Cloud Security with Virtualized Defense and Reputation-based Trust Management, in: IEEE Conference on Dependable, Autonomous, and Secure Computing (DAC-2009), Chengdu, China, 14 December 2009. Google Scholar
K. Hwang, D. Li, Trusted Cloud Computing with Secure Resources and Data Coloring, in: IEEE Internet Computing, Special Issue on Trust and Reputation Management, September 2010, pp. 14-22. Google Scholar
Kelton Research, Server Energy & Efficiency Report. www.1e.com/EnergyCampaign/downloads/Server_ Energy_and_Efficiency_Report_2009.pdf, September 2009.Google Scholar
D. Kirk, W. Hwu, Programming Massively Processors: A Hands-on Approach, Morgan Kaufmann, 2010. Google ScholarDigital Library
Y.C. Lee, A.Y. Zomaya, A Novel State Transition Method for Metaheuristic-Based Scheduling in Heterogeneous Computing Systems, in: IEEE Transactions on Parallel and Distributed Systems, September 2008. Google Scholar
Z.Y. Li, G. Xie, K. Hwang, Z.C. Li, Churn-Resilient Protocol for Massive Data Dissemination in P2P Networks, in: IEEE Trans. Parallel and Distributed Systems, May 2011. Google Scholar
X. Lou, K. Hwang, Collusive Piracy Prevention in P2P Content Delivery Networks, in: IEEE Trans. on Computers, July, 2009, pp. 970-983. Google ScholarDigital Library
NVIDIA Corp. Fermi: NVIDIA's Next-Generation CUDA Compute Architecture, White paper, 2009.Google Scholar
D. Peleg, Distributed Computing: A Locality-Sensitive Approach, SIAM, 2000. Google ScholarDigital Library
G.F. Pfister, In Search of Clusters, Second ed., Prentice-Hall, 2001. Google Scholar
J. Qiu, T. Gunarathne, J. Ekanayake, J. Choi, S. Bae, H. Li, et al., Hybrid Cloud and Cluster Computing Paradigms for Life Science Applications, in: 11th Annual Bioinformatics Open Source Conference BOSC 2010, 9-10 July 2010.Google Scholar
M. Rosenblum, T. Garfinkel, Virtual machine monitors: current technology and future trends, IEEE Computer (May) (2005) 39-47. Google ScholarDigital Library
M. Rosenblum, Recent Advances in Virtual Machines and Operating Systems, Keynote Address, ACM ASPLOS 2006.Google Scholar
J. Smith, R. Nair, Virtual Machines, Morgan Kaufmann, 2005.Google Scholar
B. Sotomayor, R. Montero, I. Foster, Virtual Infrastructure Management in Private and Hybrid Clouds, IEEE Internet Computing, September 2009. Google Scholar
SRI. The Internet of Things, in: Disruptive Technologies: Global Trends 2025, www.dni.gov/nic/PDF_GIF_Confreports/disruptivetech/appendix_F.pdf, 2010.Google Scholar
A. Tanenbaum, Distributed Operating Systems, Prentice-Hall, 1995. Google Scholar
I. Taylor, From P2P to Web Services and Grids, Springer-Verlag, London, 2005.Google Scholar
Twister, Open Source Software for Iterative MapReduce, http://www.iterativemapreduce.org/.Google Scholar
Wikipedia. Internet of Things, http://en.wikipedia.org/wiki/Internet_of_Things, June 2010.Google Scholar
Wikipedia. CUDA, http://en.wikipedia.org/wiki/CUDA, March 2011.Google Scholar
Wikipedia. TOP500, http://en.wikipedia.org/wiki/TOP500, February 2011.Google Scholar
Y. Wu, K. Hwang, Y. Yuan, W. Zheng, Adaptive Workload Prediction of Grid Performance in Confidence Windows, in: IEEE Trans. on Parallel and Distributed Systems, July 2010. Google Scholar
Z. Zong, Energy-Efficient Resource Management for High-Performance Computing Platforms, Ph.D. dissertation, Auburn University, 9 August 2008. Google Scholar
N. Adiga, et al., An overview of the blue gene/L supercomputer, in: ACM Supercomputing Conference 2002, November 2002, http://SC-2002.org/paperpdfs/pap.pap207.pdf. Google ScholarDigital Library
D. Bader, R. Pennington, Cluster computing applications, Int. J. High Perform. Comput. (May) (2001). Google Scholar
M. Baker, et al., Cluster computing white paper. http://arxiv.org/abs/cs/0004014, January 2001.Google Scholar
A. Barak, A. Shiloh, The MOSIX Management Systems for Linux Clusters, Multi-Clusters and Clouds. White paper, www.MOSIX.org//txt_pub.html, 2010.Google Scholar
A. Barak, R. La'adan, The MOSIX multicomputer operating systems for high-performance cluster computing, Future Gener. Comput. Syst. 13 (1998) 361-372. Google ScholarDigital Library
L. Barroso, J. Dean, U. Holzle, Web search for a planet: The Google cluster architecture, IEEE Micro. 23 (2) (2003) 22-28. Google ScholarDigital Library
R. Buyya (Ed.), High-Performance Cluster Computing. Vols. 1 and 2, Prentice Hall, New Jersey, 1999.Google Scholar
O. Celebioglu, R. Rajagopalan, R. Ali, Exploring InfiniBand as an HPC cluster interconnect, (October) (2004).Google Scholar
Cray, Inc, CrayXT System Specifications. www.cray.com/Products/XT/Specifications.aspx, January 2010.Google Scholar
B. Dally, GPU Computing to Exascale and Beyond, Keynote Address, ACM Supercomputing Conference, November 2010.Google Scholar
J. Dongarra, Visit to the National Supercomputer Center in Tianjin, China, Technical Report, University of Tennessee and Oak Ridge National Laboratory, 20 February 2011.Google Scholar
J. Dongarra, Survey of present and future supercomputer architectures and their interconnects, in: International Supercomputer Conference, Heidelberg, Germany, 2004.Google Scholar
K. Hwang, H. Jin, R.S. Ho, Orthogonal striping and mirroring in distributed RAID for I/O-Centric cluster computing, IEEE Trans. Parallel Distrib. Syst. 13 (2) (2002) 26-44. Google ScholarDigital Library
K. Hwang, Z. Xu, Support of clustering and availability, in: Scalable Parallel Computing, McGraw-Hill, 1998, Chapter 9.Google ScholarDigital Library
K. Hwang, C.M. Wang, C.L. Wang, Z. Xu, Resource scaling effects on MPP performance: STAP benchmark implications, IEEE Trans. Parallel Distrib. Syst. (May) (1999) 509-527. Google ScholarDigital Library
K. Hwang, H. Jin, E. Chow, C.L. Wang, Z. Xu, Designing SSI clusters with hierarchical checkpointing and single-I/O space, IEEE Concurrency (January) (1999) 60-69. Google ScholarDigital Library
H. Jin, K. Hwang, Adaptive sector grouping to reduce false sharing of distributed RAID clusters, J. Clust. Comput. 4 (2) (2001) 133-143. Google ScholarDigital Library
J. Kevin, et al., Entering the petaflop era: the architecture of performance of Roadrunner, www.c3.lanl .gov/~kei/mypubbib/papers/SC08:Roadrunner.pdf, November 2008.Google Scholar
V. Kindratenko, et al., GPU Clusters for High-Performance Computing, National Center for Supercomputing Applications, University of Illinois at Urban-Champaign, Urbana, IL, 2009.Google Scholar
K. Kopper, The Linux Enterprise Cluster: Building a Highly Available Cluster with Commodity Hardware and Free Software, No Starch Press, San Francisco, CA, 2005. Google Scholar
S.W. Lin, R.W. Lau, K. Hwang, X. Lin, P.Y. Cheung, Adaptive parallel Image rendering on multiprocessors and workstation clusters. IEEE Trans. Parallel Distrib. Syst. 12 (3) (2001) 241-258. Google ScholarDigital Library
J. Liu, D.K. Panda, et al., Performance comparison of MPI implementations over InfiniBand, Myrinet and Quadrics, (2003).Google Scholar
R. Lucke, Building Clustered Linux Systems, Prentice Hall, New Jersey, 2005. Google Scholar
E. Marcus, H. Stern, Blueprints for High Availability: Designing Resilient Distributed Systems, Wiley. Google Scholar
TOP500.org. Top-500 World's fastest supercomputers, www.top500.org, November 2010.Google Scholar
G.F. Pfister, In Search of Clusters, second ed., Prentice-Hall, 2001. Google Scholar
N.H. Sun, China's Nebulae Supercomputer, Institute of Computing Technology, Chinese Academy of Sciences, July 2010.Google Scholar
Wikipedia, IBM Roadrunner. http://en.wikipedia.org/wiki/IBM_Roadrunner, 2010, (accessed 10.01.10).Google Scholar
Wikipedia, Tianhe-1. http://en.wikipedia.org/wiki/Tianhe-1, 2011, (accessed 5.02.11).Google Scholar
Wikipedia, MOSIX. http://en.wikipedia.org/wiki/MOSIX, 2011, (accessed 10.02.11).Google Scholar
Wikipedia, CUDA. http://en.wikipedia.org/wiki/CUDA, 2011, (accessed 19.02.11).Google Scholar
K. Wong, M. Franklin, Checkpointing in distributed computing systems, J. Parallel Distrib. Comput. (1996) 67-75. Google ScholarDigital Library
Z. Xu, K. Hwang, Designing superservers with clusters and commodity components. Annual Advances in Scalable Computing, World Scientific, Singapore, 1999.Google Scholar
Z. Xu, K. Hwang, MPP versus clusters for scalable computing, in: Proceedings of the 2nd IEEE International Symposium on Parallel Architectures, Algorithms, and Networks, June 1996, pp. 117-123. Google Scholar
S. Zhou, LSF: Load Sharing and Batch Queuing Software, Platform Computing Corp., Canada, 1996.Google Scholar
Advanced Micro Devices. AMD Secure Virtual Machine Architecture Reference Manual, 2008.Google Scholar
K. Adams, O. Agesen, A comparison of software and hardware techniques for x86 virtualization, in: Proceedings of the 12th International Conference on Architectural Support for Programming Languages and Operating Systems, San Jose, CA, October 2006, pp. 21-25. Google ScholarDigital Library
V. Adve, C. Lattner, et al., LLVA: A low-level virtual instruction set architecture, in: Proceedings of the 36th International Symposium on Micro-architecture (MICRO-36 '03), 2003. Google ScholarCross Ref
J. Alonso, L. Silva, A. Andrzejak, P. Silva, J. Torres, High-available grid services through the use of virtualized clustering, in: Proceedings of the 8th Grid Computing Conference, 2007. Google Scholar
P. Anedda, M. Gaggero, et al., A general service-oriented approach for managing virtual machine allocation, in: Proceedings of the 24th Annual ACM Symposium on Applied Computing (SAC 2009), ACM Press, March 2009, pp. 9-12. Google ScholarCross Ref
H. Andre Lagar-Cavilla, J.A. Whitney, A. Scannell, et al., SnowFlock: rapid virtual machine cloning for cloud computing, in: Proceedings of EuroSystems, 2009. Google Scholar
P. Barham, B. Dragovic, K. Fraser, et al., Xen and the art of virtualization, in: Proceedings of the 19th ACM Symposium on Operating System Principles (SOSP19), ACM Press, 2003, pp. 164-177. Google ScholarDigital Library
E. Bugnion, S. Devine, M. Rosenblum, Disco: running commodity OS on scalable multiprocessors, in: Proceedings of SOSP, 1997. Google Scholar
R. Buyya, J. Broberg, A. Goscinski (Eds.), Cloud Computing: Principles and Paradigms, Wiley Press, New York, 2011. Google Scholar
V. Chadha, R. Illikkal, R. Iyer, I/O Processing in a virtualized platform: a simulation-driven approach, in: Proceedings of the 3rd International Conference on Virtual Execution Environments (VEE), 2007. Google ScholarDigital Library
R. Chandra, N. Zeldovich, C. Sapuntzakis, M.S. Lam, The collective: a cache-based system management architecture, in: Proceedings of the Second Symposium on Networked Systems Design and Implementation (NSDI '05), USENIX, Boston, May 2005, pp. 259-272. Google Scholar
J. Chase, L. Grit, D. Irwin, J. Moore, S. Sprenkle, Dynamic virtual cluster in a grid site manager, in: IEEE Int'l Symp. on High Performance Distributed Computing, (HPDC-12), 2003. Google Scholar
D. Chisnall, The Definitive Guide to the Xen Hypervisor, Prentice Hall, International, 2007. Google ScholarDigital Library
C. Clark, K. Fraser, S. Hand, et al., Live migration of virtual machines, in: Proceedings of the Second Symposium on Networked Systems Design and Implementation (NSDI '05), 2005, pp. 273-286. Google Scholar
Y. Dong, J. Dai, et al., Towards high-quality I/O virtualization, in: Proceedings of SYSTOR 2009, The Israeli Experimental Systems Conference, 2009. Google Scholar
E. Elnozahy, M. Kistler, R. Rajamony, Energy-efficient server clusters, in: Proceedings of the 2nd Workshop on Power-Aware Computing Systems, February 2002. Google ScholarDigital Library
J. Frich, et al., On the potential of NoC virtualization for multicore chips, in: IEEE Int'l Conf. on Complex, Intelligent and Software-Intensive Systems, 2008, pp. 801-807. Google Scholar
T. Garfinkel, M. Rosenblum, A virtual machine introspection-based architecture for intrusion detection, 2002.Google Scholar
L. Grit, D. Irwin, A. Yumerefendi, J. Chase, Virtual machine hosting for networked clusters: building the foundations for autonomic orchestration, in: First International Workshop on Virtualization Technology in Distributed Computing (VTDC), November 2006. Google ScholarDigital Library
D. Gupta, S. Lee, M. Vrable, et al., Difference engine: Harnessing memory redundancy in virtual machines, in: Proceedings of the USENIX Symposium on Operating Systems Design and Implementation (OSDI '08), 2008, pp. 309-322. Google Scholar
M. Hines, K. Gopalan, Post-copy based live virtual machine migration using adaptive pre-paging and dynamic self-ballooning, in: Proceedings of the ACM/USENIX International Conference on Virtual Execution Environments (VEE '09), 2009, pp. 51-60. Google Scholar
T. Hirofuchi, H. Nakada, et al., A live storage migration mechanism over WAN and its performance evaluation, in: Proceedings of the 4th International Workshop on Virtualization Technologies in Distributed Computing, 15 June, ACM Press, Barcelona, Spain, 2009. Google ScholarDigital Library
K. Hwang, D. Li, Trusted cloud computing with secure resources and data coloring, IEEE Internet Comput., (September/October) (2010) 30-39. Google Scholar
Intel Open Source Technology Center, System Virtualization--Principles and Implementation, Tsinghua University Press, Beijing, China, 2009.Google Scholar
X. Jiang, D. Xu, VIOLIN: Virtual internetworking on overlay infrastructure, in: Proceedings of the International Symposium on Parallel and Distributed Processing and Applications, 2004, pp. 937-946. Google ScholarDigital Library
H. Jin, L. Deng, S. Wu, X. Shi, X. Pan, Live virtual machine migration with adaptive memory compression, in: Proceedings of the IEEE International Conference on Cluster Computing, 2009.Google ScholarCross Ref
K. Jin, E. Miller, The effectiveness of deduplication on virtual machine disk images, in: Proceedings of SYSTOR, 2009, The Israeli Experimental Systems Conference, 2009. Google ScholarDigital Library
S. Jones, A. Arpaci-Disseau, R. Arpaci-Disseau, Geiger: Monitoring the buffer cache in a virtual machine environment, in: ACM ASPLOS, San Jose, CA, October 2006, pp. 13-14. Google Scholar
F. Kamoun, Virtualizing the datacenter without compromising server performance, ACM Ubiquity 2009, (9) (2009). Google Scholar
D. Kim, H. Kim, J. Huh, Virtual snooping: Filtering snoops in virtualized multi-coures, in: 43rd Annual IEEE/ACM Int'l Symposium on Mcrosrchitecture (MICRO-43). Google Scholar
A. Kivity, et al., KVM: The linux virtual machine monitor, in: Proceedings of the Linux Symposium, Ottawa, Canada, 2007, p. 225.Google Scholar
A. Kochut, On impact of dynamic virtual machine reallocation on data center efficiency, in: Proceedings of the IEEE International Symposium on Modeling, Analysis and Simulation of Computers and Telecommunication Systems (MASCOTS), 2008.Google ScholarCross Ref
R. Kumar, et al., Heterogeneous chip multiptiprocessors, IEEE Comput. Mag. 38 (November) (2005) 32-38. Google Scholar
B. Kyrre, Managing large networks of virtual machines, in: Proceedings of the 20th Large Installation System Administration Conference, 2006, pp. 205-214. Google Scholar
J. Lange, P. Dinda, Transparent network services via a virtual traffic layer for virtual machines, in: Proceedings of High Performance Distributed Computing, ACM Press, Monterey, CA, pp. 25-29, June 2007. Google Scholar
A. Liguori, E. Hensbergen, Experiences with content addressable storage and virtual disks, in: Proceedings of the Workshop on I/O Virtualization (WIOV '08), 2008. Google Scholar
H. Liu, H. Jin, X. Liao, L. Hu, C. Yu, Live migration of virtual machine based on full system trace and replay, in: Proceedings of the 18th International Symposium on High Performance Distributed Computing (HPDC '09), 2009, pp. 101-110. Google ScholarDigital Library
A. Mainwaring, D. Culler, Design challenges of virtual networks: Fast, general-purpose communication, in: Proceedings of the Seventh ACM SIGPLAN Symposium on Principles and Practices of Parallel Programming, 1999. Google Scholar
M. Marty, M. Hill, Virtual hierarchies to support server consolidation, in: Proceedings of the 34th Annual International Symposium on Computer Architecture (ISCA), 2007. Google ScholarDigital Library
M. McNett, D. Gupta, A. Vahdat, G.M. Voelker, Usher: An extensible framework for managing clusters of virtual machines, in: 21st Large Installation System Administration Conference (LISA) 2007. Google Scholar
D. Menasce, Virtualization: Concepts, applications., performance modeling, in: Proceedings of the 31st International Computer Measurement Group Conference, 2005, pp. 407-414.Google Scholar
A. Menon, J. Renato, Y. Turner, Diagnosing performance overheads in the Xen virtual machine environment, in: Proceedings of the 1st ACM/USENIX International Conference on Virtual Execution Environments, 2005. Google ScholarDigital Library
D. Meyer, et al., Parallax: Virtual disks for virtual machines, in: Proceedings of EuroSys, 2008. Google Scholar
J. Nick, Journey to the private cloud: Security and compliance, in: Technical presentation by EMC Visiting Team, May 25, Tsinghua University, Beijing, 2010.Google Scholar
D. Nurmi, et al., The eucalyptus open-source cloud computing system, in: Proceedings of the 9th IEEE ACM International Symposium on Cluster Computing and The Grid (CCGrid), Shanghai, China, September 2009, pp. 124-131. Google ScholarDigital Library
P. Padala, et al., Adaptive control of virtualized resources in utility computing environments, in: Proceedings of EuroSys 2007. Google ScholarDigital Library
L. Peterson, A. Bavier, M.E. Fiuczynski, S. Muir, Experiences Building PlanetLab, in: Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation (OSDI2006), 6-8 November 2006. Google Scholar
B. Pfaff, T. Garfinkel, M. Rosenblum, Virtualization aware file systems: Getting beyond the limitations of virtual disks, in: Proceedings of USENIX Networked Systems Design and Implementation (NSDI 2006), May 2006, pp. 353-366. Google Scholar
E. Pinheiro, R. Bianchini, E. Carrera, T. Heath, Dynamic cluster reconfiguration for power and performance, in: L. Benini (Ed.), Compilers and Operating Systems for Low Power, Kluwer Academic Publishers, 2003. Google ScholarDigital Library
H. Qian, E. Miller, et al., Agility in virtualized utility computing, in: Proceedings of the Third International Workshop on Virtualization Technology in Distributed Computing (VTDC 2007), 12 November 2007. Google ScholarDigital Library
H. Raj, I. Ganev, K. Schwan, Self-Virtualized I/O: High Performance, Scalable I/O Virtualization in Multi-core Systems, Technical Report GIT-CERCS-06-02, CERCS, Georgia Tech, 2006, www.cercs. gatech.edu/tech-reports/tr2006/git-cercs-06-02.pdf.Google Scholar
J. Robin, C. Irvine, Analysis of the Intel pentium's ability to support a secure virtual machine monitor, in: Proceedings of the 9th USENIX Security Symposium Vol. 9, 2000. Google ScholarCross Ref
M. Rosenblum, The reincarnation of virtual machines, ACM QUEUE, (July/August) (2004). Google Scholar
M. Rosenblum, T. Garfinkel, Virtual machine monitors: current technology and future trends, IEEE Comput 38 (5) (2005) 39-47. Google ScholarDigital Library
P. Ruth, et al., Automatic Live Migration of Virtual Computational Environments in a Multidomain Infrastructure, Purdue University, 2006.Google Scholar
C. Sapuntzakis, R. Chandra, B. Pfaff, et al., Optimizing the migration of virtual computers, in: Proceedings of the 5th Symposium on Operating Systems Design and Implementation, Boston, 9-11 December 2002. Google ScholarDigital Library
L. Shi, H. Chen, J. Sun, vCUDA: GPU accelerated high performance computing in virtual machines, in: Proceedings of the IEEE International Symposium on Parallel and Distributed Processing, 2009. Google Scholar
J. Smith, R. Nair, Virtual Machines: Versatile Platforms for Systems and Processes, Morgan Kaufmann, 2005. Google ScholarDigital Library
J. Smith, R. Nair, The architecture of virtual machines, IEEE Comput., (May) (2005). Google Scholar
Y. Song, H. Wang, et al., Multi-tiered on-demand resource scheduling for VM-based data center, in: Proceedings of the 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, 2009. Google ScholarDigital Library
B. Sotomayor, K. Keahey, I. Foster, Combining batch execution and leasing using virtual machines, in: Proceedings of the 17th International Symposium on High-Performance Distributed Computing, 2008. Google ScholarDigital Library
M. Steinder, I. Whalley, et al., Server virtualization in autonomic management of heterogeneous workloads, ACM SIGOPS Oper. Syst. Rev. 42 (1) (2008) 94-95. Google ScholarDigital Library
M. Suleman, Y. Patt, E. Sprangle, A. Rohillah, Asymmetric chip multiprocessors: balancing hardware efficiency and programming efficiency, (2007).Google Scholar
Sun Microsystems. Solaris Containers: Server Virtualization and Manageability, Technical white paper, September 2004.Google Scholar
SWsoft, Inc. OpenVZ User's Guide, http://ftp.openvz.org/doc/OpenVZ-Users-Guide.pdf, 2005.Google Scholar
F. Trivino, et al., Virtualizing netwoirk on chip resources in chip multiprocessors, J. Microprocess. Microsyst. 35 (2010). 245-230 http://www.elsevier.com/locate/micro. Google Scholar
J. Xu, M. Zhao, et al., On the use of fuzzy modeling in virtualized datacenter management, in: Proceedings of the 4th International Conference on Autonomic Computing (ICAC07), 2007. Google Scholar
R. Ublig, et al., Intel virtualization technology, IEEE Comput., (May) (2005). Google Scholar
H. Van, F. Tran, Autonomic virtual resource management for service hosting platforms, CLOUD (2009).Google Scholar
A. Verma, P. Ahuja, A. Neogi, pMapper: Power and migration cost aware application placement in virtualized systems, in: Proceedings of the 9th International Middleware Conference, 2008, pp. 243-264. Google ScholarDigital Library
VMware (white paper). Understanding Full Virtualization, Paravirtualization, and Hardware Assist, www.vmware.com/files/pdf/VMware_paravirtualization.pdf.Google Scholar
VMware (white paper). The vSphere 4 Operating System for Virtualizing Datacenters, News release, February 2009, www.vmware.com/products/vsphere/, April 2010.Google Scholar
J. Walters, et al., A comparison of virtualization technologies for HPC, in: Proceedings of Advanced Information Networking and Applications (AINA), 2008. Google ScholarDigital Library
P. Wells, K. Chakraborty, G.S. Sohi, Dynamic heterogeneity and the need for multicore virtualization, ACM SIGOPS Operat. Syst. Rev. 43 (2) (2009) 5-14. Google ScholarDigital Library
T. Wood, G. Levin, P. Shenoy, Memory buddies: Exploiting page sharing for smart collocation in virtualized data centers, in: Proceedings of the 5th International Conference on Virtual Execution Environments (VEE), 2009. Google Scholar
J. Xun, K. Chen, W. Zheng, Amigo file system: CAS based storage management for a virtual cluster system, in: Proceedings of IEEE 9th International Conference on Computer and Information Technology (CIT), 2009. Google ScholarDigital Library
Y. Yu, OS-level Virtualization and Its Applications, Ph.D. dissertation, Computer Science Department, SUNY, Stony Brook, New York, December 2007. Google Scholar
Y. Yu, F. Guo, et al., A feather-weight virtual machine for windows applications, in: Proceedings of the 2nd International Conference on Virtual Execution Environments (VEE), Ottawa, Canada, 14-16 June 2006. Google ScholarDigital Library
M. Zhao, J. Zhang, et al., Distributed file system support for virtual machines in grid computing, in: Proceedings of High Performance Distributed Computing, 2004. Google Scholar
K. Aberer, Z. Despotovic, Managing trust in a peer-to-peer information system, in: ACM CIKM International Conference on Information and Knowledge Management, 2001. Google Scholar
M. Al-Fares, A. Loukissas, A. Vahdat, A scalable, commodity datacenter network architecture, in: Proceedings of the ACM SIGCOMM 2008 Conference on Data Communication, Seattle, WA, 17-22 August 2008. Google ScholarDigital Library
Amazon EC2 and S3. Elastic Compute Cloud (EC2) and Simple Scalable Storage (S3). http://spatten_ presentations.s3.amazonaws.com/s3-on-rails.pdf.Google Scholar
M. Armbrust, A. Fox, R. Griffith, et al., Above the Clouds: A Berkeley View of Cloud Computing, Technical Report No. UCB/EECS-2009-28, University of California at Berkley, 10 February 2009.Google Scholar
I. Arutyun, et al., Open circus: a global cloud computing testbed, IEEE Comput. Mag. (2010) 35-43. Google Scholar
P. Barham, et al., Xen and the art of virtualization, in: Proceedings of the 19th ACM Symposium on Operating System Principles, ACM Press, New York, 2003. Google ScholarDigital Library
L. Barroso, J. Dean, U. Holzle, Web search for a planet: the architecture of the Google cluster, IEEE Micro (2003), doi: 10.1109/MM.2003.1196112. Google Scholar
L. Barroso, U. Holzle, The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines, Morgan Claypool Publishers, 2009. Google ScholarCross Ref
G. Boss, P. Mllladi, et al., Cloud computing: the bluecloud project. www.ibm.com/developerworks/websphere/zones/hipods/, 2007.Google Scholar
R. Buyya, J. Broberg, A. Goscinski (Eds.), Cloud Computing: Principles and Paradigms, Wiley Press, 2011. Google Scholar
R. Buyya, C.S. Yeo, S. Venugopal, Market-oriented cloud computing: vision, hype, and reality for delivering IT services as computing utilities, in: Proceedings of the 10th IEEE International Conference on High Performance Computing and Communications (HPCC), Dalian, China, 25-27 September 2008. Google Scholar
R. Buyya, R. Ranjan, R.N. Calheiros, InterCloud: utility-oriented federation of cloud computing environments for scaling of application services, in: Proceedings of the 10th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2010, LNCS 608), Busan, South Korea, 21-23 May 2010. Google ScholarDigital Library
M. Cai, K. Hwang, J. Pan, C. Papadopoulos, WormShield: fast worm signature generation with distributed fingerprint aggregation, in: IEEE Transactions of Dependable and Secure Computing (TDSC), Vol. 4, No. 2, April/June 2007, pp. 88-104. Google ScholarDigital Library
Chase, et al., Dynamic virtual clusters in a grid site manager, in: IEEE 12th Symposium on High-Performance Distributed Computing (HPDC), 2003. Google Scholar
Y. Chen, K. Hwang, W.S. Ku, Collaborative detection of DDoS attacks over multiple network domains, in: IEEE Transaction on Parallel and Distributed Systems, Vol. 18, No. 12, December 2007, pp. 1649-1662. Google ScholarDigital Library
T. Chou, Introduction to Cloud Computing: Business and Technology, Active Book Press, 2010.Google Scholar
C. Clark, K. Fraser, J. Hansen, et al., Live migration of virtual machines, in: Proceedings of the Second Symposium on Networked Systems Design and Implementation, Boston, MA, 2 May 2005, pp. 273-286. Google ScholarDigital Library
Cloud Computing Tutorial. www.thecloudtutorial.com, January 2010.Google Scholar
Cloud Security Alliance, Security guidance for critical areas of focus in cloud computing, April 2009.Google Scholar
C. Collberg, C. Thomborson, Watermarking, temper-proofing, and obfuscation tools for software protection, IEEE Trans. Software Eng. 28 (2002) 735-746. Google ScholarDigital Library
A. Costanzo, M. Assuncao, R. Buyya, Harnessing cloud technologies for a virtualized distributed computing infrastructure, IEEE Internet Comput. (2009). Google Scholar
D. Dyer, Current trends/Challenges in datacenter thermal management--A facilities perspective, in: Presentation at ITHERM, San Diego, 1 June 2006.Google Scholar
Q. Feng, K. Hwang, Y. Dai, Rainbow product ranking for upgrading e-commerce, IEEE Internet Comput. (2009). Google Scholar
I. Foster, The grid: computing without bounds, Sci. Am. 288 (4) (2003) 78-85.Google ScholarCross Ref
I. Foster, Y. Zhao, J. Raicu, S. Lu, Cloud computing and grid computing 360-degree compared, in: Grid Computing Environments Workshop, 12-16 November 2008.Google ScholarCross Ref
D. Gannon, The client+cloud: changing the paradigm for scientific research, Keynote address, in: CloudCom 2010, Indianapolis, 2 November 2010.Google Scholar
Google Inc, Efficient data center summit. www.google.com/corporate/green/datacenters/summit.html, 2009.Google Scholar
Green Grid, Quantitative analysis of power distribution configurations for datacenters. www.thegreengrid .org/gg_content/.Google Scholar
A. Greenberg, J. Hamilton, D. Maltz, P. Patel, The cost of a cloud: research problems in datacenter networks, in: ACM SIGCOMM Computer Communication Review, Vol. 39, No. 1, January 2009. Google Scholar
C. Guo, G. Lu, et al., BCube: a high-performance server-centric network architecture for modular datacenters, in: ACM SIGCOMM Computer Communication Review, Vol. 39, No. 44, October 2009. Google Scholar
E. Hakan, Cloud computing: does Nirvana hide behind the Nebula? IEEE Softw. (2009). Google Scholar
B. Hayes, Cloud computing, Commun. ACM 51 (2008) 9-11. Google ScholarDigital Library
C. Hoffa, et al., On the use of cloud computing for scientific workflows, in: IEEE Fourth International Conference on eScience, December 2008. Google ScholarDigital Library
R. He, J. Hu, J. Niu, M. Yuan, A novel cloud-based trust model for pervasive computing, in: Fourth International Conference on Computer and Information Technology, 14-16 September 2004, pp. 693-700. Google ScholarDigital Library
K. Hwang, S. Kulkarni, Y. Hu, Cloud security with virtualized defense and reputation-based trust management, in: IEEE International Conference on Dependable, Autonomic, and Secure Computing (DASC 09), Chengdu, China, 12-14 December 2009. Google Scholar
K. Hwang, D. Li, Trusted cloud computing with secure resources and data coloring, IEEE Internet Comput. (2010). Google Scholar
K. Hwang, M. Cai, Y. Chen, M. Qin, Hybrid intrusion detection with weighted signature generation over anomalous internet episodes, in: IEEE Transactions on Dependable and Secure Computing, Vol.4, No.1, January-March 2007, pp. 41-55. Google ScholarDigital Library
V. Jinesh, Cloud Architectures, White paper, Amazon. http://aws.amazon.com/about-aws/whats-new/2008/07/16/cloud-architectures-white-paper/.Google Scholar
D. Kamvar, T. Schlosser, H. Garcia-Molina, The EigenTrust algorithm for reputation management in P2P networks, in: Proceedings of the 12th International Conference on the World Wide Web, 2003. Google ScholarDigital Library
K. Keahey, M. Tsugawa, A. Matsunaga, J. Fortes, Sky computing, IEEE Internet Comput., (2009). Google Scholar
Kivit, et al., KVM: the linux virtual machine monitor, in: Proceedings of the Linux Symposium, Ottawa, Canada, 2007, p. 225.Google Scholar
KVM Project, Kernel-based virtual machines. www.linux-kvm.org, 2011 (accessed 02.11).Google Scholar
G. Lakshmanan, Cloud Computing: Relevance to Enterprise, Infosys Technologies, Inc., 2009.Google Scholar
N. Leavitt, et al., Is cloud computing really ready for prime time? IEEE Comput. 42 (1) (2009) 15-20. Google ScholarDigital Library
D. Li, H. Meng, X. Shi, Membership clouds and membership cloud generator, J. Comput. Res. Dev. 32 (6) (1995) 15-20.Google Scholar
D. Li, C. Liu, W. Gan, A new cognitive model: cloud model, Int. J. Intell. Syst. (2009). Google Scholar
D. Linthicum, Cloud Computing and SOA Convergence in Your Enterprise: A Step-by-Step Guide, Addison Wesley Professional, 2009. Google Scholar
X. Lou, K. Hwang, Collusive piracy prevention in P2P content delivery networks, IEEE Trans. Comput., (2009). Google Scholar
M. Luis, Vaquero, L. Rodero-Merino, et al., A break in the clouds: towards a cloud definition, in: ACM SIGCOMM Computer Communication Review Archive, January 2009. Google Scholar
D. Manchala, E-Commerce trust metrics and models, IEEE Internet Comput. (2000). Google Scholar
T. Mather, et al., Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance, O'Reilly Media, Inc., 2009. Google Scholar
L. Mei, W. Chan, T. Tse, A tale of clouds: paradigm comparisons and some thoughts on research issues, in: IEEE Asia-Pacific Services Computing Conference, December 2008. Google ScholarDigital Library
D. Nelson, M. Ryan, S. DeVito, et al., The role of modularity in datacenter design, Sun BluePrints. www.sun .com/storagetek/docs/EED.pdf.Google Scholar
M. Nelson, B.H. Lim, G. Hutchins, Fast transparent migration for virtual machines, in: Proceedings of the USENIX 2005 Annual Technical Conference, Anaheim, CA, 10-15 April 2005, pp. 391-394. Google Scholar
D. Nurmi, R. Wolski, et al., Eucalyptus: an Elastic utility computing architecture linking your programs to useful systems, in: UCSB Computer Science Technical Report No. 2008-10, August 2008.Google Scholar
W. Norman, M. Paton, T. de Aragao, et al., Optimizing utility in cloud computing through autonomic workload execution, in: Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 2009.Google Scholar
D.A. Patterson, et al., Recovery-Oriented Computing (ROC): Motivation, Definition, Techniques, and Case Studies, UC Berkeley CS Technical Report UCB//CSD-02-1175, 15 March 2002. Google Scholar
M. Pujol, et al., Extracting reputation in multi-agent systems by means of social network topology, in: Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems, 2002. Google ScholarDigital Library
S. Roschke, F. Cheng, C. Meinel, Intrusion detection in the cloud, in: IEEE International Conference on Dependable, Autonomic, and Secure Computing (DASC 09), 13 December 2009. Google Scholar
R. Raghavendra, P. Ranganathan, V. Talwar, Z. Wang, X. Zhu, No 'power' struggles: coordinated multi-level power management for the datacenter, in: Proceedings of the ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Seattle, WA, March 2008. Google Scholar
D. Reed, Clouds, clusters and many core: the revolution ahead, in: Proceedings of the 2008 IEEE International Conference on Cluster Computing, 29 September-1 October 2008.Google ScholarCross Ref
J. Rittinghouse, J. Ransome, Cloud Computing: Implementation, Management, and Security, CRC Publishers, 2010. Google Scholar
B. Rochwerger, D. Breitgand, E. Levy, et al., The RESERVOIR Model and Architecture for Open Federated Cloud Computing, IBM Syst. J. (2008). Google Scholar
R.N. Calheiros, R. Ranjan, C.A.F. De Rose, R. Buyya, CloudSim: a novel framework for modeling and simulation of cloud computing infrastructures and services, Technical Report, GRIDS-TR-2009-1, University of Melbourne, Australia, 13 March 2009.Google Scholar
Salesforce.com, http://en.wikipedia.org/wiki/Salesforce.com/, 2010.Google Scholar
H. Shen, K. Hwang, Locality-preserving clustering and discovery of resources in wide-area computational grids, IEEE Trans. Comput. (2011) Accepted To Appear. Google Scholar
S. Song, K. Hwang, R. Zhou, Y. Kwok, Trusted P2P transactions with fuzzy reputation aggregation, in: IEEE Internet Computing, Special Issue on Security for P2P and Ad Hoc Networks, November 2005, pp. 24-34. Google Scholar
B. Sotomayor, R. Montero, I. Foster, Virtual infrastructure management in private and hybrid clouds, IEEE Internet Comput. (2009). Google Scholar
G. Stuer, K. Vanmechelena, J. Broeckhovea, A commodity market algorithm for pricing substitutable grid resources, Future Gener. Comput. Syst. 23 (5) (2007) 688-701. Google ScholarDigital Library
C. Vecchiola, X. Chu, R. Buyya, Aneka: a software platform for.NET-based cloud computing, in: W. Gentzsch, et al. (Eds.), High Speed and Large Scale Scientific Computing, IOS Press, Amsterdam, Netherlands, 2009, pp. 267-295.Google Scholar
T. Velte, A. Velite, R. Elsenpeter, Cloud Computing, A Practical Approach, McGraw-Hill Osborne Media, 2010. Google Scholar
S. Venugopal, X. Chu, R. Buyya, A negotiation mechanism for advance resource reservation using the alternate offers protocol, in: Proceedings of the 16th International Workshop on Quality of Service (IWQoS 2008), Twente, The Netherlands, June 2008.Google ScholarCross Ref
K. Vlitalo, Y. Kortesniemi, Privacy in distributed reputation management, in: Workshop of the 1st Int'l Conference on Security and Privacy for Emerging Areas in Communication Networks, September 2005.Google Scholar
VMware, Inc., Disaster Recovery Solutions from VMware, White paper, www.vmware.com/, 2007 (accessed 07).Google Scholar
VMware, Inc., Migrating Virtual Machines with Zero Downtime, www.vmware.com/, 2010 (accessed 07).Google Scholar
VMware, Inc., vSphere, www.vmware.com/products/vsphere/, 2010 (accessed 02.10).Google Scholar
L. Vu, M. Hauswirth, K. Aberer, QoS-based service selection and ranking with trust and reputation management, in: Proceedings of the On The Move Conference (OTM '05), LNCS 3760, 2005. Google Scholar
W. Voosluys, et al., Cost of VM live migration in clouds: a performance evaluation, in: Proceedings of the First International Conference on Cloud Computing, IOS Press, Netherlands, 2009, pp. 267-295. Google Scholar
Y. Wang, J. Vassileva, Toward trust and reputation based web service selection: a survey, J. Multi-agent Grid Syst. (MAGS) (2007).Google Scholar
Wikipedia, Cloud computing, http://en.wikipedia.org/wiki/Cloud_computing, 2010 (accessed 26.01.10).Google Scholar
Wikipedia, Data center, http://en.wikipedia.org/wiki/Data_center, 2010 (accessed 26.01.10).Google Scholar
H. Wu, G. Lu, D. Li, C. Guo, Y. Zhang, MDCube: a high performance network structure for modular data center interconnection, ACM CoNEXT '09, Rome, 1-4 December 2009. Google ScholarDigital Library
Y. Wu, K. Hwang, Y. Yuan, W. Zheng, Adaptive workload prediction of grid performance in confidence windows, IEEE Trans. Parallel Distrib. Syst. (2010). Google Scholar
XEN Organization, www.sen.org, 2011 (accessed 20.02.11).Google Scholar
L. Xiong, L. Liu, PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities, IEEE Trans. Knowl. Data Eng. (2004) 843-857. Google Scholar
J. Yang, J. Wang, C. Wang, D. Li., A novel scheme for watermarking natural language text, in: Proceedings of the Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2007, pp. 481-484. Google ScholarDigital Library
L. Youseff, M. Butrico, D. Maria, D. Silva, Toward a unified ontology of cloud computing, in: Grid Computing Environments Workshop (GCE '08), November 2008, pp. 1-10.Google Scholar
F. Zhang, J. Cao, K. Hwang, C. Wu, Ordinal optimized scheduling of scientific workflows in elastic compute Clouds, IEEE Trans. Comput. (2011) submitted (under review).Google Scholar
R. Zhou, K. Hwang, PowerTrust: a robust and scalable reputation system for trusted peer-to-peer computing, IEEE Trans. Parallel Distrib. Syst. (2007). Google Scholar
D. Booth, H. Haas, F. McCabe, et al., Working Group Note 11: Web Services Architecture, www.w3 .org/TR/2004/NOTE-ws-arch-20040211/ (accessed 18.10.10).Google Scholar
R. Fielding, Architectural Styles and the Design of Network-Based Software Architectures, University of California at Irvine, 2000, p. 162, http://portal.acm.org/citation.cfm?id=932295. Google Scholar
M. Hadley, Web Application Description Language (WADL), W3C Member Submission, www.w3.org/Submission/wadl/, 2009 (accessed 18.10.10).Google Scholar
Restlet, the leading RESTful web framework for Java, www.restlet.org/ (accessed 18.10.10).Google Scholar
JSR 311-JAX-RS: Java API for RESTful Web Services, https://jsr311.dev.java.net/ (accessed 18.10.10).Google Scholar
Jersey open source, production quality, JAX-RS (JSR 311) reference implementation for building RESTful web services, https://jersey.dev.java.net/ (accessed 18.10.10).Google Scholar
D. Winer, The XML-RPC specification, www.xmlrpc.com/, 1999 (accessed 18.10.10).Google Scholar
L. Richardson, S. Ruby, RESTful Web Services, O'Reilly, 2007. Google Scholar
A. Nadalin, C. Kaler, R. Monzillo, P. Hallam-Baker, Web services security: SOAP message security 1.1 (WS-Security 2004), OASIS Standard Specification, http://docs.oasis-open.org/wss/v1.1/wss-v1.1-spec-os-SOAPMessageSecurity.pdf, 2006 (accessed 18.10.10).Google Scholar
A. Andrieux, K. Czajkowski, A. Dan, et al., Web services agreement specification (WS-Agreement), OGF Documents, GFD.107, www.ogf.org/documents/GFD.107.pdf, 2007 (accessed 18.10.2010).Google Scholar
D. Davis, A. Karmarkar, G. Pilz, S. Winkler, Ü. Yalçinalp, Web services reliable messaging (WS-Reliable-Messaging), OASIS Standard, http://docs.oasis-open.org/ws-rx/wsrm/200702, 2009 (accessed 18.10.2010).Google Scholar
M. Little, A. Wilkinson, Web services atomic transaction (WS-AtomicTransaction) Version 1.2, OASIS Standard, http://docs.oasis-open.org/ws-tx/wstx-wsat-1.2-spec-os.pdf, 2009.Google Scholar
M. Feingold, R. Jeyaraman, Web services coordination (WS-Coordination) Version 1.2, OASIS Standard, http://docs.oasis-open.org/ws-tx/wstx-wscoor-1.2-spec-os.pdf, 2009 (accessed 18.10.2010).Google Scholar
K. Chiu, M. Govindaraju, R. Bramley, Investigating the limits of SOAP performance for scientific computing, in: 11th IEEE International Symposium on High Performance Distributed Computing, 2002, pp. 246-254. Google ScholarCross Ref
D. Gannon, G. Fox, Workflow in grid systems, Editorial of special issue of Concurrency & Computation: Practice & Experience, based on GGF10 Berlin meeting, Vol. 18, No. 10, 2006, pp. 1009-1019, doi: http://dx.doi.org/10.1002/cpe.v18:10 and http://grids.ucs.indiana.edu/ptliupages/publications/Workflow-overview.pdf. Google Scholar
JBPM Flexible business process management (BPM) suite, www.jboss.org/jbpm (accessed 18.10.10).Google Scholar
JBoss enterprise middleware, www.jboss.org/ (accessed 18.10.10).Google Scholar
Taverna workflow management system, www.taverna.org.uk/ (accessed 18.10.10).Google Scholar
R.V. Englen, K. Gallivan, The gSOAP toolkit for web services and peer-to-peer computing networks, in: 2nd IEEE/ACM International Symposium on Cluster Computing and The Grid (CCGRID '02), 2002. Google ScholarCross Ref
R. Salz, ZSI: The zolera soap infrastructure, http://pywebsvcs.sourceforge.net/zsi.html, 2005 (accessed 18.10.10).Google Scholar
J. Edwards, 3-Tier server/client at work, first ed., John Wiley & Sons, 1999.Google Scholar
B. Sun, A multi-tier architecture for building RESTful web services, IBM Developer Works 2009, www. ibm.com/developerworks/web/library/wa-aj-multitier/index.html, 2009 (accessed 18.10.2010).Google Scholar
G. Alonso, F. Casati, H. Kuno, V. Machiraju, Web Services: Concepts, Architectures and Applications (Data-Centric Systems and Applications), Springer Verlag, 2010. Google Scholar
I. Foster, H. Kishimoto, A. Savva, et al., The open grid services architecture version 1.5, Open Grid Forum, GFD.80, www.ogf.org/documents/GFD.80.pdf, 2006.Google Scholar
I. Foster, S. Tuecke, C. Kesselman, The philosophy of the grid, in: 1st International Symposium on Cluster Computing and the Grid (CCGRID0), IEEE Computer Society, 2001.Google Scholar
S. Tuecke, K. Czajkowski, I. Foster, et al., Grid Services Infrastructure (OGSI) Version 1.0. Global Grid Forum Proposed Recommendation, GFD15, www.ggf.org/documents/GFD.15.pdf, 2003 (accessed 18.10.10).Google Scholar
S. Graham, A. Karmarkar, J. Mischkinsky, I. Robinson, I. Sedukhin, Web Services Resource 1.2 (WS-Resource) WSRF, OASIS Standard, http://docs.oasis-open.org/wsrf/wsrf-ws_resource-1.2-spec-os.pdf, 2006 (accessed 18.10.10).Google Scholar
M. Gudgin, M. Hadley, T. Rogers, Web Services Addressing 1.0-Core, W3C Recommendation, 9 May 2006.Google Scholar
G. Fox, D. Gannon, A Survey of the Role and Use of Web Services and Service Oriented Architectures in Scientific/Technical Grids, http://grids.ucs.indiana.edu/ptliupages/publications/ReviewofServices and Workflow-IU-Aug2006B.pdf, 2006 (accessed 16.10.10).Google Scholar
Supported version of Mule ESB, www.mulesoft.com/.Google Scholar
Open source version of Mule ESB, www.mulesoft.org/.Google Scholar
IBM's original network software MQSeries rebranded WebSphereMQ in 2002, http://en.wikipedia.org/wiki/IBM_WebSphere_MQ.Google Scholar
WebSphereMQ IBM network software, http://en.wikipedia.org/wiki/IBM_WebSphere_MQ.Google Scholar
H. Shen, Content-based publish/subscribe systems, in: X. Shen, et al., (Eds.), Handbook of Peer-to-Peer Networking, Springer Science+Business Media, LLC, 2010, pp. 1333-1366.Google ScholarCross Ref
Java Message Service JMS API, www.oracle.com/technetwork/java/index-jsp-142945.html and http://en .wikipedia.org/wiki/Java_Message_Service.Google Scholar
AQMP Open standard for messaging middleware, www.amqp.org/confluence/display/AMQP/Advanced+ Message+Queuing+Protocol.Google Scholar
Mule MQ open source enterprise-class Java Message Service (JMS) implementation, www.mulesoft.org/documentation/display/MQ/Home.Google Scholar
Apache ActiveMQ open source messaging system, http://activemq.apache.org/.Google Scholar
NaradaBrokering open source content distribution infrastructure, www.naradabrokering.org/.Google Scholar
RabbitMQ open source Enterprise Messaging System, www.rabbitmq.com/.Google Scholar
Amazon Simple Queue Service (Amazon SQS), http://aws.amazon.com/sqs/.Google Scholar
Microsoft Azure Queues, http://msdn.microsoft.com/en-us/windowsazure/ff635854.aspx.Google Scholar
N. Wilkins-Diehr, Special issue: Science gateways-common community interfaces to grid resources, Concurr. Comput. Pract. Exper. 19 (6) (2007) 743-749. Google ScholarDigital Library
N. Wilkins-Diehr, D. Gannon, G. Klimeck, S. Oster, S. Pamidighantam, TeraGrid science gateways and their impact on science, Computer 41 (11) (2008). Google Scholar
Y. Liu, S. Wang, N. Wilkins-Diehr, SimpleGrid 2.0: A learning and development toolkit for building highly usable TeraGrid science gateways, in: SC-GCE, 2009. Google Scholar
D.A. Reed, Grids, the TeraGrid and beyond, IEEE Comput. 36 (1) (2003) 62-68. Google ScholarDigital Library
R. Pordes, D. Petravick, B. Kramer, et al., The open science grid, J. Phys. Conf. Ser. 78 (2007) 012057.Google ScholarCross Ref
I. Foster, Globus toolkit version 4: software for service-oriented systems, J. Comput. Sci. Technol. 21 (4) (2006) 513-520.Google Scholar
D. Thain, T. Tannenbaum, M. Livny, Distributed computing in practice: the condor experience, Concurr. Pract. Exper. 17 (2-4) (2005) 323-356. Google ScholarCross Ref
IRODS: Data Grids, Digital Libraries, Persistent Archives, and Real-time Data Systems, https://www .irods.org (accessed 29.08.10).Google Scholar
J. Basney, M. Humphrey, V. Welch, The MyProxy online credential repository, Softw. Pract. Exp. 35 (9) (2005) 801-816. Google ScholarDigital Library
J.V. Welch, J. Basney, D. Marcusiu, N. Wilkins-Diehr, A AAAA model to support science gateways with community accounts, Concurr. Comput. Pract. Exper., (2006) 893-904. Google Scholar
L. Liming, et al., TeraGrid's integrated information service, in: 5th Grid Computing Environments Workshop, ACM, 2009. Google Scholar
J. Kim, P.V. Sudhakar, Computational Chemistry Grid, a Production Cyber-environment through Distributed Computing: Recent Enhancements and Application for DFT Calculation of Amide I Spectra of Amyloid-Fibril. PRAGMA13, Urbana, IL, 2007.Google Scholar
R. Dooley, K. Milfeld, C. Guiang, S. Pamidighantam, G. Allen, From proposal to production: lessons learned developing the computational chemistry grid cyberinfrastructure, J. Grid Comput. 4 (2) (2006) 195-208.Google ScholarCross Ref
GridChem-Related Scientific Publications, https://www.gridchem.org/papers.Google Scholar
B. Demeler, UltraScan: A comprehensive data analysis software package for analytical ultracentrifugation experiments, in: Analytical Ultracentrifugation:Techniques and Methods, 2005, pp. 210-229.Google Scholar
UltraScan Gateway, http://uslims.uthscsa.edu/.Google Scholar
UltraScan publications database, www.ultrascan.uthscsa.edu/search-refs.html.Google Scholar
E.H. Brookes, R.V. Boppana, B. Demeler, Biology-Computing large sparse multivariate optimization problems with an application in biophysics, in: ACM/IEEE Conference on Supercomputing (SC2006), Tampa FL, 2006. Google ScholarDigital Library
E.H. Brookes, B. Demeler, Parsimonious regularization using genetic algorithms applied to the analysis of analytical ultracentrifugation experiments, in: 9th Annual Conference on Genetic and Evolutionary Computation (GECCO), London, 2007, pp. 361-368. Google ScholarCross Ref
G. Klimeck, M. McLennan, S.P. Brophy, et al., nanoHUB.org: Advancing education and research in nanotechnology, Comput. Sci. Eng. 10 (5) (2008) 17-23. Google ScholarDigital Library
A. Strachan, G. Klimeck, M.S. Lundstrom, Cyber-enabled simulations in nanoscale science and engineering, Comput. Sci. Eng. 12 (2010) 12-17. Google ScholarDigital Library
H. Abelson, The creation of OpenCourseWare at MIT, J. Sci. Educ. Technol. 17 (2) (2007) 164-174.Google ScholarCross Ref
T. J. Hacker, R. Eigenmann, S. Bagchi, A. Irfanoglu, S. Pujol, A. Catlin, Ellen Rathje, The NEEShub cyberinfrastructure for earthquake engineering, computing, in Science and Engineering, 13 (4) (2011) 67-78, doi:10.1109/MCSE.2011.70. Google ScholarDigital Library
T. Richardson, Q. Stafford-Fraser, K.R. Wood, A. Hopper, Virtual network computing, IEEE Internet Comput. 2 (1) (1998) 33-38. Google ScholarDigital Library
P.M. Smith, T.J. Hacker, C.X. Song, Implementing an industrial-strength academic cyberinfrastructure at Purdue University, in: IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2008.Google Scholar
W. Qiao, M. McLennan, R. Kennell, D. Ebert, G. Klimeck, Hub-based simulation and graphics hardware accelerated visualization for nanotechnology applications, IEEE Trans. Vis. Comput. Graph. 12 (2006) 1061-1068. Google ScholarDigital Library
G. Klimeck, M. Luisier, Atomistic modeling of realistically extended semiconductor devices with NEMO/OMEN, IEEE Comput. Sci. Eng. 12 (2010) 28-35. Google ScholarDigital Library
B.P. Haley, G. Klimeck, M. Luisier, et al., Computational nanoelectronics research and education at nanoHUB.org, J. Comput. Electron. 8 (2009) 124-131.Google ScholarCross Ref
OpenVZ web site, http://openvz.org (accessed 17.08.10).Google Scholar
J. Alameda, M. Christie, G. Fox, et al., The open grid computing environments collaboration: portlets and services for science gateways, Concurr. Comput. Pract. Exper. 19 (6) (2007) 921-942. Google ScholarDigital Library
Open Grid Computing Environments web site, www.collab-ogce.org (accessed 18.10.10).Google Scholar
Z. Guo, R. Singh, M.E. Pierce, Building the PolarGrid portal using Web 2.0 and OpenSocial, in: SC-GCE, 2009. Google ScholarDigital Library
T. Gunarathne, C. Herath, E. Chinthaka, S. Marru, Experience with adapting a WS-BPEL runtime for eScience workflows, in: 5th Grid Computing Environments Workshop, ACM, 2009. Google ScholarDigital Library
S. Marru, S. Perera, M. Feller, S. Martin, Reliable and Scalable Job Submission: LEAD Science Gateways Testing and Experiences with WS GRAM on TeraGrid Resources, in: TeraGrid Conference, 2008.Google Scholar
S. Perera, S. Marru, T. Gunarathne, D. Gannon, B. Plale, Application of management frameworks to manage workflow-based systems: A case study on a large scale e-science project, in: IEEE International Conference on Web Services, 2009. Google Scholar
S. Perera, S. Marru, C. Herath, Workflow Infrastructure for Multi-scale Science Gateways, in: TeraGird Conference, 2008.Google Scholar
T. Andrews, F. Curbera, H. Dholakia, et al., Business process execution language for web services, version 1.1, 2003.Google Scholar
T. Oinn, M. Addis, J. Ferris, et al., Taverna: a tool for the composition and enactment of bioinformatics workflows, Bioinformatics, (2004). Google Scholar
E. Deelman, J. Blythe, Y. Gil, et al., Pegasus: Mapping scientific workflows onto the grid, in: Grid Computing, Springer, 2004.Google Scholar
Apache ODE (Orchestration Director Engine) open source BPEL execution engine, http://ode.apache.org/.Google Scholar
M. Christie, S. Marru, The LEAD Portal: a TeraGrid gateway and application service architecture, Concurr. Comput. Pract. Exper. 19 (6) (2007) 767-781. Google ScholarDigital Library
UDDI Version 3 Specification, OASIS Standard, OASIS UDDI Specifications TC-Committee Specifications, www.oasis-open.org/committees/uddi-spec/doc/tcspecs.htm#uddiv3, 2005 (accessed 18.10.10).Google Scholar
Programmable Web site for contributed service APIs and mashups, www.programmableweb.com/ (accessed 18.10.10).Google Scholar
J. Gregorio, B. de hOra, RFC 5023-The Atom Publishing Protocol, IETF Request for Comments, http://tools.ietf.org/html/rfc5023, 2007 (accessed 18.10.10).Google Scholar
L. Vargas, J. Bacon, Integrating Databases with Publish/Subscribe, in: 25th IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW '05), 2005. Google Scholar
M. Aktas, Thesis. Information Federation in Grid Information Services. Indiana University, http://grids .ucs.indiana.edu/ptliupages/publications/MehmetAktasThesis.pdf, 2007. Google Scholar
M.S. Aktas, G.C. Fox, M. Pierce, A federated approach to information management in grids, J. Web Serv. Res. 7 (1) (2010) 65-98, http://grids.ucs.indiana.edu/ptliupages/publications/JWSR-PaperRevisedSubmission529- Proofread.pdf. Google ScholarDigital Library
M.S. Aktas, M. Pierce, High-performance hybrid information service architecture, Concurr. Comput. Pract. Exper. 22 (15) (2010) 2095-2123. Google ScholarDigital Library
E. Deelman, G. Singh, M.P. Atkinson, et al., Grid based metadata services, in: 16th International Conference on Scientific and Statistical Database Management (SSDBM '04), Santorini, Greece, 2004. Google ScholarDigital Library
C.K. Baru, The SDSC Storage Resource Broker, in: I. Press, (Ed.), CASCON '98 Conference, Toronto, 1998. Google Scholar
G. Singh, S. Bharathi, A. Chervenak, et al., A Metadata Catalog Service for Data Intensive Applications, in: 2003 ACM/IEEE Conference on Supercomputing, Conference on High Performance Networking and Computing, ACM Press, 15-21 November 2003, p. 17. Google Scholar
L. Chervenak, et al., Performance and Scalability of a Replica Location Service, in: 13th IEEE International Symposium on High Performance Distributed Computing (HPDC 13), IEEE Computer Society, Washington, DC, 2004, pp. 182-191. Google ScholarDigital Library
B. Koblitz, N. Santos, V. Pose, The AMGA metadata service, J. Grid Comput. 6 (1) (2007) 61-76.Google ScholarCross Ref
C.A. Goble, D. De Roure, The Semantic Grid: Myth busting and bridge building, in: 16th European Conference on Artificial Intelligence (ECAI-2004), Valencia, Spain, 2004.Google Scholar
O. Corcho, et al., An Overview of S-OGSA: A Reference Semantic Grid Architecture, in: Journal of Web Semantics: Science, Services and Agents on the World Wide Web, 2006, pp. 102-115. Google ScholarDigital Library
MyGrid, www.mygrid.org.uk/.Google Scholar
J. Dean, S. Ghemawat, MapReduce: Simplified Data Processing on Large Clusters, in: Sixth Symposium on Operating Systems Design and Implementation, 2004, pp. 137-150. Google Scholar
M. Isard, M. Budiu, Y. Yu, A. Birrell, D. Fetterly, Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks, in: ACM SIGOPS Operating Systems Review, ACM Press, Lisbon, Portugal, 2007. Google Scholar
S. Ghemawat, The Google File System, in: 19th ACM Symposium on Operating System Principles, 2003, pp. 20-43. Google Scholar
D. Thain, T. Tannenbaum, M. Livny, Distributed computing in practice: the Condor experience, Concurr. Comput. Pract. Exper. 17 (2-4) (2005) 323-356. Google ScholarDigital Library
D. Gelernter, Generative communication in Linda, in: ACM Transactions on Programming Languages and Systems, 1985, pp. 80-112. Google ScholarDigital Library
E. Freeman, S. Hupfer, K. Arnold, JavaSpaces: Principles, Patterns, and Practice, Addison-Wesley, 1999. Google ScholarDigital Library
F. Chang, et al., BigTable: A Distributed Storage System for Structured Data, in: OSDI 2006, Seattle, pp. 205-218. Google ScholarDigital Library
G. De Candia, et al., Dynamo: Amazon's highly available key-value store, in: SOSP, Stevenson, WA, pp. 205-219.Google Scholar
R. Van Renesse, K. Birman, W. Vogels, Astrolabe: A robust and scalable technology for distributed system monitoring, management, and data mining, in: ACM Transactions on Computer Systems, 2003, pp. 164-206. Google ScholarDigital Library
J. Yu, R. Buyya, A taxonomy of workflow management systems for grid computing, in: Technical Report, GRIDS-TR-2005-1, Grid Computing and Distributed Systems Laboratory, University of Melbourne, Australia, 2005.Google ScholarCross Ref
I.J. Taylor, E. Deelman, D.B. Gannon, M. Shields, Workflows for e-Science: Scientific Workflows for Grids, Springer, 2006. Google ScholarDigital Library
Z. Zhao, A. Belloum, M. Bubak, Editorial: Special section on workflow systems and applications in e-Science, Future Generation Comp. Syst. 25 (5) (2009) 525-527, http://dx.doi.org/10.1016/j.future.2008.10.011. Google ScholarDigital Library
E. Deelman, D. Gannon, M. Shields, I. Taylor, Workflows and e-Science: an overview of workflow system features and capabilities, Future Generation Comp. Syst. 25 (5) (2009) 528-540, doi: http://dx.doi .org/10.1016/j.future.2008.06.012. Google ScholarDigital Library
Workflow Management Consortium, www.wfmc.org/.Google Scholar
R. Allen, Workflow: An Introduction, Workflow Handbook. Workflow Management Coalition, 2001.Google Scholar
N. Carriero, D. Gelernter, Linda in context, Commun. ACM 32 (4) (1989) 444-458. Google ScholarDigital Library
A. Beguelin, J. Dongarra, G.A. Geist, HeNCE: A User's Guide, Version 2.0, www.netlib.org/hence/hence-2.0-doc-html/hence-2.0-doc.html.Google Scholar
C. Upson, T. Faulhaber Jr., D.H. Laidlaw, et al., The application visualization system: a computational environment for scientific visualization, IEEE Comput. Graph. Appl., (1989) 30-42. Google ScholarDigital Library
J. Rasure, S. Kubica, The Khoros application development environment, in: Khoral Research Inc., Albuquerque, New Mexico, 1992.Google Scholar
A. Hoheisel, User tools and languages for graph-based Grid workflows, Concurr. Comput. Pract. Exper. 18 (10) (2006) 1101-1113, http://dx.doi.org/10.1002/cpe.v18:10. Google ScholarDigital Library
Z. Guan, F. Hernandez, P. Bangalore, et al., Grid-Flow: A Grid-enabled scientific workflow system with a Petri-net-based interface, Concurr. Comput. Pract. Exper. 18 (10) (2006) 1115-1140, http://dx.doi.org/10.1002/cpe.v18:10. Google ScholarDigital Library
M. Kosiedowski, K. Kurowski, C. Mazurek, J. Nabrzyski, J. Pukacki, Workflow applications in GridLab and PROGRESS projects, Concurr. Comput. Pract. Exper. 18 (10) (2006) 1141-1154, http://dx.doi.org/10.1002/cpe.v18:10. Google ScholarDigital Library
LabVIEW Laboratory Virtual Instrumentation Engineering Workbench, http://en.wikipedia.org/wiki/LabVIEW.Google Scholar
LabSoft LIMS laboratory information management system, www.labsoftlims.com/.Google Scholar
LIMSource Internet LIMS resource, http://limsource.com/home.html.Google Scholar
InforSense Business Intelligence platform, hwww.inforsense.com/products/core_technology/inforsense_ platform/index.html.Google Scholar
Pipeline Pilot scientific informatics platform from Accelrys, http://accelrys.com/products/pipeline-pilot/.Google Scholar
OASIS Web Services Business Process Execution Language Version 2.0 BPEL, http://docs.oasis-open .org/wsbpel/2.0/OS/wsbpel-v2.0-OS.html.Google Scholar
F. Curbera, R. Khalaf, W.A. Nagy, S. Weerawarana, Implementing BPEL4WS: The architecture of a BPEL4WS implementation, Concurr. Comput. Pract. Exper. 18 (10) (2006) 1219-1228, http://dx.doi.org/10.1002/cpe.v18:10. Google ScholarDigital Library
ActiveBPEL Open Source workflow engine, www.activebpel.org/.Google Scholar
F. Leyman, Choreography for the Grid: Towards fitting BPEL to the resource framework, Concurr. Comput. Pract. Exper. 18 (10) (2006) 1201-1217, http://dx.doi.org/10.1002/cpe.v18:10. Google ScholarCross Ref
R. Barga, D. Guo, J. Jackson, N. Araujo, Trident: a scientific workflow workbench, in: Tutorial eScience Conference, Indianapolis, 2008. Google Scholar
Microsoft, Project Trident: A Scientific Workflow Workbench, http://tridentworkflow.codeplex.com/and http://research.microsoft.com/en-us/collaboration/tools/trident.aspx.Google Scholar
The forecast before the storm. [iSGTW International Science Grid This Week], www.isgtw.org/? pid=1002719, 2010.Google Scholar
C. Goble, Curating services and workflows: the good, the bad and the ugly, a personal story in the small, in: European Conference on Research and Advanced Technology for Digital Libraries, 2008.Google Scholar
Linked Environments for Atmospheric Discovery II (LEAD II), http://pti.iu.edu/d2i/leadII-home.Google Scholar
XBaya workflow composition tool, www.collab-ogce.org/ogce/index.php/XBaya.Google Scholar
XBaya integration with OGCE Open Grid Computing Environments Portal, www.collab-ogce.org/ogce/index.php/XBaya.Google Scholar
V. Bhat, M. Parashar, Discover middleware substrate for integrating services on the grid, in: Proceedings of the 10th International Conference on High Performance Computing (HiPC 2003), Lecture Notes in Computer Science. Springer-Verlag, Hyderabad, India, 2003.Google ScholarCross Ref
Z. Zhao, A. Belloum, C.D. Laat, P. Adriaans, B. Hertzberger, Distributed execution of aggregated multidomain workflows using an agent framework, in: IEEE Congress on Services (Services 2007), 2007.Google ScholarCross Ref
Open source scripting workflow supporting the many task execution paradigm, www.ci.uchicago.edu/swift/.Google Scholar
L. Ramakrishnan, B. Plale, A multi-dimensional classification model for scientific workflow characteristics, in: 1st International Workshop on Workflow Approaches to New Data-Centric Science, Indianapolis, 2010. Google ScholarDigital Library
Kepler Open Source Scientific Workflow System, http://kepler-project.org.Google Scholar
B. Ludäscher, I. Altintas, C. Berkley, et al., Scientific workflow management and the Kepler system, Concurr. Comput. Pract. Exper. 18 (10) (2006) 1039-1065, http://dx.doi.org/10.1002/cpe.v18:10. Google ScholarDigital Library
T. McPhillips, S. Bowers, D. Zinn, B. Ludäscher, Scientific workflow design for mere mortals, Future Generation Comp. Syst. 25 (5) (2009) 541-551, http://dx.doi.org/10.1016/j.future.2008.06.013. Google ScholarDigital Library
Triana, Triana Open Source Problem Solving Environment, www.trianacode.org/index.html (accessed 18.10.10).Google Scholar
I. Taylor, M. Shields, I. Wang, A. Harrison, in: I. Taylor, et al., (Eds.), Workflows for e-Science, Springer, 2007, pp. 320-339.Google ScholarCross Ref
D. Churches, G. Gombas, A. Harrison, et al., Programming scientific and distributed workflow with Triana services, Concurr. Comput. Pract. Exper. 18 (10) (2006) 1021-1037, http://dx.doi.org/10.1002/cpe.v18:10. Google ScholarDigital Library
Pegasus Workflow Management System, http://pegasus.isi.edu/.Google Scholar
T. Oinn, M. Greenwood, M. Addis, et al., Taverna: Lessons in creating a workflow environment for the life sciences, Concurr. Comput. Pract. Exper. 18 (10) (2006) 1067-1100, http://dx.doi.org/10.1002/cpe .v18:10. Google ScholarDigital Library
myGrid multi-institutional, multi-disciplinary research group focusing on the challenges of eScience, www.mygrid.org.uk/.Google Scholar
OMII UK Software Solutions for e-Research, www.omii.ac.uk/index.jhtml.Google Scholar
Collaborative workflow social networking site, www.myexperiment.org/.Google Scholar
H. Gadgil, G. Fox, S. Pallickara, M. Pierce, Managing grid messaging middleware, in: Challenges of Large Applications in Distributed Environments (CLADE), 2006, pp. 83-91.Google Scholar
HPSearch, Scripting environment for managing streaming workflow and their messaging based communication, www.hpsearch.org/, 2005 (accessed 18.10.10).Google Scholar
C. Herath, B. Plale, Streamflow, in: 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, 2010.Google Scholar
Many Task Computing Paradigm, http://en.wikipedia.org/wiki/Many-task_computing.Google Scholar
D. Bhatia, V. Burzevski, M. Camuseva, et al., WebFlow: A visual programming paradigm for web/Java based coarse grain distributed computing, Concurr. Comput. Pract. Exper. 9 (6) (1997) 555-577.Google ScholarCross Ref
IBM WebSphere sMash Web 2.0 Workflow system, IBM DeveloperWorks, www.ibm.com/developerworks/websphere/zones/smash/ (accessed 19.10.10).Google Scholar
Common Component Architecture CCA Forum, www.cca-forum.org/.Google Scholar
D. Gannon, S. Krishnan, L. Fang, et al., On building parallel & grid applications: component technology and distributed services, Cluster Comput. 8 (4) (2005) 271-277, http://dx.doi.org/10.1007/s10586-005-4094-2. Google ScholarDigital Library
E. Deelman, T. Kosar, C. Kesselman, M. Livny, What makes workflows work in an opportunistic environment? Concurr. Comput. Pract. Exper. 18 (10) (2006), http://dx.doi.org/10.1002/cpe.v18:10. Google Scholar
Condor home page, www.cs.wisc.edu/condor/.Google Scholar
Karajan parallel scripting language, http://wiki.cogkit.org/index.php/Karajan.Google Scholar
GridAnt extension of the Apache Ant build tool residing in the Globus COG kit, www.gridworkflow.org/snips/gridworkflow/space/GridAnt.Google Scholar
H. Chivers, J. McDermid, Refactoring service-based systems: How to avoid trusting a workflow service, Concurr. Comput. Pract. Exper. 18 (10) (2006) 1255-1275, http://dx.doi.org/10.1002/cpe.v18:10. Google ScholarDigital Library
S. Weerawarana, F. Curbera, F. Leymann, T. Storey, D.F. Ferguson. Web Services Platform Architecture: SOAP, WSDL, WS-Policy, WS-Addressing, WS-BPEL, WS-Reliable Messaging, and More, Prentice Hall, 2005. Google ScholarDigital Library
M. Atkinson, D. DeRoure, A. Dunlop, et al., Web Service Grids: An evolutionary approach, Concurr. Comput. Pract. Exper. 17 (2005) 377-389, http://dx.doi.org/10.1002/cpe.936. Google ScholarDigital Library
T. Segaran, C. Evans, J. Taylor, Programming the Semantic Web, O'Reilly, 2009. Google Scholar
G. Fox, Data and metadata on the semantic grid, Comput. Sci. Eng. 5 (5) (2003) 76-78. Google ScholarDigital Library
H. Gonzalez, A. Halevy, C.S. Jensen, et al., Google fusion tables: Data management, integration and collaboration in the cloud. International Conference on Management of Data, in: Proceedings of the 1st ACM Symposium on Cloud Computing, ACM, Indianapolis, 2010, pp. 175-180. Google ScholarDigital Library
C. Dabrowski, Reliability in grid computing systems, Concurr. Comput. Pract. Exper. 21 (8) (2009) 927-959. Google ScholarDigital Library
Microsoft, Project Trident: A Scientific Workflow Workbench, http://research.microsoft.com/en-us/collaboration/tools/trident.aspx, 2010.Google Scholar
W. Lu, J. Jackson, R. Barga, AzureBlast: A case study of developing science applications on the cloud, in: ScienceCloud: 1st Workshop on Scientific Cloud Computing co-located with HPDC (High Performance Distributed Computing), ACM, Chicago, IL, 21 June 2010. Google Scholar
Distributed Systems Laboratory (DSL) at University of Chicago Wiki. Performance Comparison: Remote Usage, NFS, S3-fuse, EBS. 2010.Google Scholar
D. Jensen, Blog entry on Compare Amazon S3 to EBS data read performance, http://jensendarren .wordpress.com/2009/12/30/compare-amazon-s3-to-ebs-data-read-performance/, 2009.Google Scholar
Zend PHP Company, The Simple Cloud API for Storage, Queues and Table, http://www.simplecloud.org/home, 2010.Google Scholar
Microsoft, Windows Azure Geo-location Live, http://blogs.msdn.com/b/windowsazure/archive/2009/04/30/windows-azure-geo-location-live.aspx, 2009.Google Scholar
Raytheon BBN, SHARD (Scalable, High-Performance, Robust and Distributed) Triple Store based on Hadoop. http://www.cloudera.com/blog/2010/03/how-raytheon-researchers-are-using-hadoop-to-build-ascalable-distributed-triple-store/, 2010.Google Scholar
NOSQL Movement, Wikipedia list of resources, http://en.wikipedia.org/wiki/NoSQL, 2010.Google Scholar
NOSQL Link Archive, LIST OF NOSQL DATABASES, http://nosql-database.org/, 2010.Google Scholar
F. Chang, J. Dean, S. Ghemawat, W.C. Hsieh, D. Wallach, M. Burrows, et al., BigTable: A distributed storage system for structured data, in: OSDI'06: Seventh Symposium on Operating System Design and Implementation, USENIX, Seattle, WA, 2006. Google Scholar
Amazon, Welcome to Amazon SimpleDB, http://docs.amazonwebservices.com/AmazonSimpleDB/latest/DeveloperGuide/index.html, 2010.Google Scholar
J. Haridas, N. Nilakantan, B. Calder, Windows Azure Table, http://go.microsoft.com/fwlink/?LinkId=153401, 2009.Google Scholar
International Virtual Observatory Alliance, VOTable Format Definition Version 1.1, http://www.ivoa.net/Documents/VOTable/20040811/, 2004.Google Scholar
Apache Incubator, Heart (Highly Extensible & Accumulative RDF Table) planet-scale RDF data store and a distributed processing engine based on Hadoop & Hbase, http://wiki.apache.org/incubator/HeartProposal, 2010.Google Scholar
M. King, Amazon SimpleDB and CouchDB Compared, http://www.automatthew.com/2007/12/amazon-simpledb-and-couchdb-compared.html, 2007.Google Scholar
Apache, Hbase implementation of BigTable on Hadoop File System, http://hbase.apache.org/, 2010.Google Scholar
Apache, The CouchDB document-oriented database project, http://couchdb.apache.org/index.html, 2010.Google Scholar
M/Gateway Developments Ltd, M/DB Open Source "plug-compatible" alternative to Amazon's SimpleDB database, http://gradvs1.mgateway.com/main/index.html?path=mdb, 2009.Google Scholar
ActiveMQ, http://activemq.apache.org/, 2009.Google Scholar
S. Pallickara, G. Fox, NaradaBrokering: a distributed middleware framework and architecture for enabling durable peer-to-peer grids, in: ACM/IFIP/USENIX 2003 International Conference on Middleware, Rio de Janeiro, Brazil, Springer-Verlag, New York, Inc., 2003. Google ScholarCross Ref
NaradaBrokering, Scalable Publish Subscribe System, http://www.naradabrokering.org/, 2010.Google Scholar
Apache Hadoop, http://hadoop.apache.org/, 2009.Google Scholar
J. Ekanayake, A.S. Balkir, T. Gunarathne, G. Fox, C. Poulain, N. Araujo, et al., DryadLINQ for scientific analyses, in: Fifth IEEE International Conference on eScience, Oxford, 2009. Google ScholarDigital Library
J. Ekanayake, T. Gunarathne, J. Qiu, G. Fox, S. Beason, J.Y. Choi, et al., Applicability of DryadLINQ to Scientific Applications, Community Grids Laboratory, Indiana University, 2009.Google Scholar
M. Isard, M. Budiu, Y. Yu, A. Birrell, D. Fetterly, Dryad: Distributed data-parallel programs from sequential building blocks, in: ACM SIGOPS Operating Systems Review, ACM Press, 2007. Google Scholar
Y. Yu, M. Isard, D. Fetterly, M. Budiu, U. Erlingsson, P.K. Gunda, et al., DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language, in: Symposium on Operating System Design and Implementation (OSDI), 2008. Google ScholarDigital Library
J. Dean, S. Ghemawat, MapReduce: simplified data processing on large clusters, Commun. ACM 51 (1) (2008) 107-113. Google ScholarDigital Library
J. Ekanayake, H. Li, B. Zhang, T. Gunarathne, S. Bae, J. Qiu, et al., Twister: a runtime for iterative MapReduce, in: Proceedings of the First International Workshop on MapReduce and Its Applications of ACM HPDC 2010 conference, ACM, Chicago, IL, 20-25 June 2010. Google Scholar
T. Gunarathne, T. Wu, J. Qiu, G. Fox, MapReduce in the Clouds for Science, in: CloudCom, IUPUI Conference Center, Indianapolis, 30 November-3 December 2010. Google Scholar
R.S. Dorward, R. Griesemer, S. Quinlan, Interpreting the data: parallel analysis with Sawzall, Scientific Prog. J. 13 (4) (2005) 227-298 (Special Issue on Grids and Worldwide Computing Programming Models and Infrastructure). Google Scholar
Pig! Platform for analyzing large data sets, http://hadoop.apache.org/pig/, 2010.Google Scholar
C. Olston, B. Reed, U. Srivastava, R. Kumar, A. Tomkins, Pig Latin: a not-so-foreign language for data processing, in: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, ACM, Vancouver, Canada, 2008, pp. 1099-1110. Google ScholarDigital Library
G. Malewicz, M.H. Austern, A. Bik, J. Dehnert, I. Horn, N. Leiser, et al., Pregel: a system for large-scale graph processing, in: Proceedings of the twenty-first annual symposium on parallelism in algorithms and architectures, ACM, Calgary, Canada, 2009, p. 48. Google Scholar
Cloudera, CDH: A free, stable Hadoop distribution offering RPM, Debian, AWS and automatic configuration options. http://www.cloudera.com/hadoop/, 2010.Google Scholar
A. Grama, G. Karypis, V. Kumar, A. Gupta, Introduction to Parallel Computing, second ed., Addison Wesley, 2003.Google Scholar
J. Dean, S. Ghemawat, MapReduce: Simplified Data Processing on Large Clusters, in: Sixth Symposium on Operating Systems Design and Implementation, 2004, pp. 137-150. Google Scholar
H. Kasim, V. March, R. Zhang, S. See, Survey on Parallel Programming Model, in: IFIP International Conference on Network and Parallel Computing, Lecture Notes in Computer Science, Vol. 5245, Springer-Verlag, Shanghai, China, 2008, pp. 266-275. Google Scholar
S. Hariri, M. Parashar, Tools and Environments for Parallel and Distributed Computing, Series on Parallel and Distributed Computing, Wiley, 2004, ISBN:978-0471332886. Google Scholar
L. Silva, R. Buyya, Parallel Programming Models and Paradigms, (2007).Google Scholar
T. Gunarathne, T. Wu, J. Qiu, G. Fox, Cloud Computing Paradigms for Pleasingly Parallel Biomedical Applications, in: Proceedings of the Emerging Computational Methods for the Life Sciences Workshop of ACM HPDC 2010 conference, Chicago, IL, 20-25 June 2010. Google Scholar
G. Fox, MPI and MapReduce, in: Clusters, Clouds, and Grids for Scientific Computing CCGSC, Flat Rock, NC, http://grids.ucs.indiana.edu/ptliupages/presentations/CCGSC-Sept8-2010.pptx, 8 September 2010.Google Scholar
J. Ekanayake, X. Qiu, T. Gunarathne, S. Beason, G. Fox, High Performance Parallel Computing with Clouds and Cloud Technologies, Cloud Computing and Software Services: Theory and Techniques, CRC Press (Taylor and Francis), 2010.Google Scholar
T. Hoefler, A. Lumsdaine, J. Dongarra, Towards Efficient MapReduce Using MPI, in: Recent Advances in Parallel Virtual Machine and Message Passing Interface, Lecture Notes in Computer Science: vol. 5759, Springer Verlag, Espoo Finland, 2009, pp. 240-249. Google ScholarDigital Library
S. Ibrahim, H. Jin, B. Cheng, H. Cao, S. Wu, L. Qi, CLOUDLET: towards mapreduce implementation on virtual machines, in: Proceedings of the 18th ACM International Symposium on High Performance Distributed Computing, ACM, Garching, Germany, 2009, pp. 65-66. Google Scholar
T. Sandholm, K. Lai, MapReduce optimization using regulated dynamic prioritization, in: Proceedings of the eleventh international joint conference on measurement and modeling of computer systems, ACM, Seattle, WA, 2009, pp. 299-310. Google ScholarDigital Library
Wikipedia, MapReduce, http://en.wikipedia.org/wiki/MapReduce, 2010 (accessed 06.11.10).Google Scholar
J. Dean, S. Ghemawat, MapReduce: Simplified Data Processing on Large Clusters, in: Presentation at OSDI-2004 Conference. http://labs.google.com/papers/mapreduce-osdi04-slides/index.html, 2004 (accessed 6.11.10). Google Scholar
R. Lammel, Google's MapReduce programming model-Revisited, Sci. Comput. Prog. 68 (3) (2007) 208-237. Google ScholarDigital Library
M. Zaharia, A. Konwinski, A.D. Joseph, R. Katz, I. Stoica, Improving MapReduce performance in heterogeneous environments, in: Proceedings of the 8th USENIX conference on operating systems design and implementation, USENIX Association, San Diego, California, 2008, pp. 29-42. Google ScholarDigital Library
N. Vasic, M. Barisits, V. Salzgeber, D. Kostic, Making cluster applications energy-aware, in: Proceedings of the 1st workshop on automated control for datacenters and clouds, ACM, Barcelona, Spain, 2009, pp. 37-42. Google ScholarDigital Library
D.J. DeWitt, E. Paulson, E. Robinson, J. Naughton, J. Royalty, S. Shankar, et al., Clustera: an integrated computation and data management system, in: Proc. VLDB Endow, 2008, 1(1), pp. 28-41. Google ScholarDigital Library
S. Ghemawat, H. Gobioff, S. Leung, The Google File System, in: 19th ACM Symposium on Operating Systems Principles, 2003, pp. 20-43. Google Scholar
Google, Introduction to Parallel Programming and MapReduce, http://code.google.com/edu/parallel/mapreduce-tutorial.html, 2010.Google Scholar
J. Ekanayake, H. Li, B. Zhang, T. Gunarathne, S. Bae, J. Qiu, et al., Twister: a runtime for iterative MapReduce, in: Proceedings of the First International Workshop on MapReduce and Its Applications of ACM HPDC 2010 Conference, ACM, Chicago, IL, 20-25 June 2010. Google Scholar
B. Zhang, Y. Ruan, T. Wu, J. Qiu, A. Hughes, G. Fox, Applying Twister to Scientific Applications, in: CloudCom 2010, IUPUI Conference Center, Indianapolis, 30 November-3 December 2010. Google Scholar
G. Malewicz, M.H. Austern, A. Bik, J.C. Dehnert, I. Horn, N. Leiser, et al., Pregel: A System for Large-Scale Graph Processing, in: International conference on management of data, Indianapolis, Indiana, 2010, pp. 135-146. Google Scholar
Y. Bu, B. Howe, M. Balazinska, M.D. Ernst, HaLoop: Efficient Iterative Data Processing on Large Clusters, in: The 36th International Conference on Very Large Data Bases, VLDB Endowment, Vol. 3, Singapore, 13-17 September 2010. Google Scholar
M. Zaharia, M. Chowdhury, M.J. Franklin, S. Shenker, I. Stoica, Spark: Cluster Computing with Working Sets, in: 2nd USENIX Workshop on Hot Topics in Cloud Computing (HotCloud '10), Boston, 22 June 2010. Google ScholarDigital Library
SALSA Group, Iterative MapReduce, http://www.iterativemapreduce.org/, 2010.Google Scholar
Yahoo, Yahoo! Hadoop Tutorial, http://developer.yahoo.com/hadoop/tutorial/index.html, 2010.Google Scholar
G. Coulouris, J. Dollimore, T. Kindberg, Distributed Systems: Concepts and Design. International Computer Science Series, 4th ed., Addison-Wesley, 2004. Google Scholar
T. White, Hadoop: The Definitive Guide, Second ed., Yahoo Press, 2010. Google Scholar
Apache, HDFS Overview, http://hadoop.apache.org/hdfs/, 2010.Google Scholar
Apache, Hadoop MapReduce, http://hadoop.apache.org/mapreduce/docs/current/index.html, 2010.Google Scholar
J. Venner, Pro Hadoop, first ed., Apress, 2009, ISBN:978-1430219422. Google Scholar
Apache! Pig! (part of Hadoop), http://pig.apache.org/, 2010.Google Scholar
A. Choudhary, G. Fox, S. Hiranandani, K. Kennedy, C. Koelbel, S. Ranka, et al., Unified compilation of Fortran 77D and 90D, ACM Lett. Program. Lang. Syst. 2 (1-4) (1993) 95-114. Google ScholarDigital Library
Yahoo, Pig! Tutorial. http://developer.yahoo.com/hadoop/tutorial/module6.html#pig.Google Scholar
Systems@ETH Zurich, Massively Parallel Data Analysis with MapReduce. Lectures on MapReduce, Hadoop and Pig Latin. http://www.systems.ethz.ch/education/past-courses/hs08/map-reduce/map-reduce/lecture-slides, 2008 (accessed 07.11.10).Google Scholar
G. Fox, R.D. Williams, P.C. Messina, Parallel computing works! Morgan Kaufmann Publishers, 1994.Google Scholar
J. Ekanayake, T. Gunarathne, J. Qiu, G. Fox, S. Beason, J. Choi, et al., Applicability of DryadLINQ to Scientific Applications, Community Grids Laboratory, Indiana University, http://grids.ucs.indiana.edu/ptliupages/publications/DryadReport.pdf, 2010.Google Scholar
J. Qiu, J. Ekanayake, T. Gunarathne, J. Choi, S. Bae, Y. Ruan, et al., Data Intensive Computing for Bioinformatics, http://grids.ucs.indiana.edu/ptliupages/publications/DataIntensiveComputing_ BookChapter.pdf, 2009.Google Scholar
J. Ekanayake, T. Gunarathne, J. Qiu, Cloud Technologies for Bioinformatics Applications, IEEE Trans. Parallel Distrib. Syst., (2010). Google Scholar
J. Qiu, T. Gunarathne, J. Ekanayake, J. Choi, S. Bae, H. Li, et al., Hybrid Cloud and Cluster Computing Paradigms for Life Science Applications, in: 11th Annual Bioinformatics Open Source Conference BOSC, Boston, 9-10 July 2010.Google Scholar
M. Burrows, The Chubby Lock Service for Loosely-Coupled Distributed Systems, in: OSDI'06: Seventh Symposium on Operating System Design and Implementation, USENIX, Seattle, WA, 2006, pp. 335-350. Google Scholar
G.C. Fox, A. Ho, E. Chan, W. Wang, Measured characteristics of distributed cloud computing infrastructure for message-based collaboration applications, in: Proceedings of the 2009 International Symposium on Collaborative Technologies and Systems, IEEE Computer Society, 2009, pp. 465-467. Google ScholarDigital Library
G. DeCandia, D. Hastorun, M. Jampani, G. Kakulapati, A. Lakshman, A. Pilchin, et al., Dynamo: Amazon's highly available key-value store, SIGOPS Oper. Syst. Rev. 41 (6) (2007) 205-220. Google ScholarDigital Library
Eucalyptus LLC, White Papers. http://www.eucalyptus.com/whitepapers.Google Scholar
D. Nurmi, R. Wolski, C. Grzegorczyk, G. Obertelli, S. Soman, L. Youseff, et al., The Eucalyptus Open-Source Cloud-Computing System, in: 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGRID '09, Shanghai, 18-21 May 2009, pp. 124-131. Google Scholar
K. Keahey, I. Foster, T. Freeman, X. Zhang, Virtual workspaces: achieving quality of service and quality of life in the Grid, Scientific Prog. J. 13 (4) (2005) 265-275. Google ScholarDigital Library
Nimbus, Cloud computing for science, http://www.nimbusproject.org, 2010.Google Scholar
Nimbus, Frequently Asked Questions, http://www.nimbusproject.org/docs/current/faq.html, 2010.Google Scholar
Django, High-Level Python Web Framework, http://www.djangoproject.com/, 2010.Google Scholar
Amazon, Simple Storage Service API Reference: API Version 2006-03-01, http://awsdocs.s3.amazonaws .com/S3/latest/s3-api.pdf, 2006.Google Scholar
boto, Python interface to Amazon Web Services, http://code.google.com/p/boto/, 2010.Google Scholar
S3tools project, Open source tools for accessing Amazon S3-Simple Storage Service, http://s3tools.org/s3tools, 2010.Google Scholar
bitbucket, JetS3t: open-source Java toolkit and application suite for Amazon Simple Storage Service (Amazon S3), Amazon CloudFront content delivery network, and Google Storage. http://bitbucket.org/jmurty/jets3t/wiki/Home.Google Scholar
Amazon, Amazon Elastic Compute Cloud (Amazon EC2). http://aws.amazon.com/ec2.Google Scholar
OpenNebula, industry standard open source cloud computing tool. http://opennebula.org/.Google Scholar
I.M. Llorente, R. Moreno-Vozmediano, R.S. Montero, Cloud Computing for On-Demand Grid Resource Provisioning, in: Advances in Parallel Computing: High Speed and Large Scale Scientific Computing vol. 18, IOS Press, 2009, pp. 177-191.Google Scholar
R. Monteroa, R. Moreno-Vozmediano, I. Llorente, An elasticity model for high throughput computing clusters, J. Parallel Distrib. Comput. (May) (2010). Google Scholar
B. Sotomayor, R.S. Montero, I.M. Llorente, I. Foster, Capacity Leasing in Cloud Systems Using the OpenNebula Engine, in: 2008 Workshop on Cloud Computing and Its Applications (CCA08), Chicago, IL, 2008, http://www.cca08.org/papers/Paper20-Sotomayor.pdf.Google Scholar
libvirt, virtualization API. http://libvirt.org.Google Scholar
B. Sotomayor, R.S. Montero, I.M. Llorente, I. Foster, Virtual infrastructure management in private and hybrid clouds, IEEE Internet Comp. 13 (5) (2009) 14-22. Google ScholarDigital Library
ElasticHosts, Flexible servers in the cloud. http://www.elastichosts.com/.Google Scholar
Sector/Sphere, High Performance Distributed File System and Parallel Data Processing Engine. http://sector.sourceforge.net.Google Scholar
Y. Gu, R. Grossman, Sector/Sphere: A Distributed Storage and Computing Platform. SC08 Poster, http://sector.sourceforge.net/pub/sector-sc08-poster.pdf, 2008.Google Scholar
Y. Gu, R. Grossman, Lessons learned from a year's worth of benchmarks of large data clouds, in: Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers, ACM, Portland, Oregon, 2009, pp. 1-6. Google ScholarDigital Library
Y. Gu, R. Grossman, UDT: UDP-based data transfer for high-speed wide area networks, Comput. Netw. 51 (7) (2007) 1777-1799. Google ScholarDigital Library
FUSE, Filesystem in Userspace. http://fuse.sourceforge.net.Google Scholar
Y. Gu, R.L. Grossman, Sector and sphere: the design and implementation of a high-performance data cloud, Phil. Trans. R. Soc. A 367 (2009) 2429-2445.Google ScholarCross Ref
Open Stack, Open Source, Open Standards Cloud, http://openstack.org/index.php, 2010.Google Scholar
VSCSE, Big Data for Science. Virtual Summer School hosted by SALSA group at Indiana University, 26 July-30 July 2010, http://salsahpc.indiana.edu/tutorial/.Google Scholar
T. Hey, The Fourth Paradigm: Data-Intensive Scientific Discovery, http://research.microsoft.com/en-us/um/redmond/events/TonyHey/21216/player.htm, 2010.Google Scholar
T. Hey, S. Tansley, K. Tolle, The Fourth Paradigm: Data-Intensive Scientific Discovery, http://research .microsoft.com/en-us/collaboration/fourthparadigm/, 2009 (accessed 07.11.10).Google Scholar
SALSA Group, Catalog of Cloud Material, http://salsahpc.indiana.edu/content/cloud-materials, 2010.Google Scholar
Microsoft Research, Cloud Futures Workshop, http://research.microsoft.com/en-us/events/cloudfutures2010/default.aspx, 2010.Google Scholar
T. Chou, Introduction to Cloud Computing: Business and Technology, Active Book Press, LLC, 2010, p. 252, http://www.lulu.com/items/volume_67/8215000/8215197/1/print/8215197.pdf.Google Scholar
R. Buyya, C. Yeo, S. Venugopal, J. Broberg, I. Brandic, Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility, Future Gener. Comput. Syst. 25 (6) (2009) 599-616. Google ScholarDigital Library
P. Chaganti, Cloud computing with Amazon Web Services, Part 1: Introduction -- When it's smarter to rent than to buy, http://www.ibm.com/developerworks/architecture/library/ar-cloudaws1/, 2008.Google Scholar
Cloud computing with Amazon Web Services, Part 2: Storage in the cloud with Amazon Simple Storage Service (S3)-Reliable, flexible, and inexpensive storage and retrieval of your data, http://www.ibm .com/developerworks/architecture/library/ar-cloudaws2/, 2008.Google Scholar
P. Chaganti, Cloud computing with Amazon Web Services, Part 3: Servers on demand with EC2, http://www.ibm.com/developerworks/architecture/library/ar-cloudaws3/, 2008.Google Scholar
M.R. Palankar, A. Iamnitchi, M. Ripeanu, S. Garfinkel, Amazon S3 for science grids: a viable solution? in: Proceedings of the 2008 International Workshop on Data-aware Distributed Computing, ACM, Boston, MA, 2008, pp. 55-64. Google ScholarDigital Library
W. Sun, K. Zhang, S. Chen, X. Zhang, H. Liang, Software as a Service: An Integration Perspective, in: Fifth International Conference Service-Oriented Computing-ICSOC, Lecture Notes in Computer Science, Vol. 4749, Springer Verlag, Vienna Austria, 2007, pp. 558-569. Google Scholar
G. Lakshmanan, Cloud Computing. Relevance to Enterprise, http://www.infosys.com/cloud-computing/white-papers/Documents/relevance-enterprise.pdf, 2009.Google Scholar
N. Leavitt, Is cloud computing really ready for prime time? Computer 42 (1) (2009) 15-20. Google ScholarDigital Library
G. Lin, G. Dasmalchi, J. Zhu, Cloud Computing and IT as a Service: Opportunities and Challenges, in: Web Services, ICWS '08, IEEE, Beijing, 23-26 September 2008. Google Scholar
D.S. Linthicum, Cloud Computing and SOA Convergence in Your Enterprise: A Step-by-Step Guide, Addison-Wesley Professional, 2009. Google Scholar
L. Mei, W.K. Chan, T.H. Tse, A Tale of Clouds: Paradigm Comparisons and Some Thoughts on Research Issues, in: Asia-Pacific Services Computing Conference. APSCC '08 IEEE, Yilan, Taiwan, 9-12 December 2008, pp. 464-469. Google Scholar
G. Fox, S. Bae, J. Ekanayake, X. Qiu, H. Yuan, Parallel Data Mining from Multicore to Cloudy Grids, book chapter of High Speed and Large Scale Scientific Computing, IOS Press, Amsterdam, 2009, http://grids.ucs.indiana.edu/ptliupages/publications/CetraroWriteupJune11-09.pdf.Google Scholar
J. Ekanayake, G. Fox, High Performance Parallel Computing with Clouds and Cloud Technologies, in: First International Conference CloudComp on Cloud Computing, Munich, Germany, 2009.Google Scholar
F. Chang, J. Dean, S. Ghemawat, W.C. Hsieh, D.A. Wallach, M. Burrows, et al., BigTable: a distributed storage system for structured data, ACM Trans. Comput. Syst. 26 (2) (2008) 1-26. Google ScholarDigital Library
E. Deelman, G. Singh, M. Livny, B. Berriman, J. Good, The cost of doing science on the cloud: the Montage example, in: Proceedings of the 2008 ACM/IEEE Conference on Supercomputing, IEEE Press, Austin, Texas, 2008, pp. 1-12, http://www.csd.uwo.ca/faculty/hanan/cs843/papers/ewa-ec2.pdf. Google ScholarCross Ref
C. Hoffa, G. Mehta, T. Freeman, E. Deelman, K. Keahey, B. Berriman, et al., On the Use of Cloud Computing for Scientific Workflows, in: Proceedings of the 2008 Fourth IEEE International Conference on eScience, IEEE Computer Society, 2008, pp. 640-645. Google ScholarDigital Library
N. Paton, A. Marcelo, T. De Aragão, K. Lee, A. Alvaro, R. Sakellariou, Optimizing utility in cloud computing through autonomic workload execution, Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, http://www.cs.man.ac.uk/~alvaro/publications/TCDEBull09.pdf, 2009.Google Scholar
B. Rochwerger, et al., The Reservoir model and architecture for open federated cloud computing, IBM J. Res. Dev. 53 (4) (2009) 4:1-4:11. Google ScholarDigital Library
W. Allcock, J. Bresnahan, R. Kettimuthu, et al., The globus striped gridFTP framework and server, in: Proceedings of the ACM/IEEE Conference on Supercomputing, 2005. Google ScholarCross Ref
R. Aydt, D. Gunter, W. Smith, et al., A Grid Monitoring Architecture, Global Grid Forum Performance Working Group, 2002.Google Scholar
F. Azzedin, M. Maheswaran, A trust brokering system and its application to resource management in public-resource grids, in: Proceedings of the 18th International Parallel and Distributed Processing Symposium (IPDPS '04), Santa Fe, NM, April 26, 2004, p. 22a.Google ScholarCross Ref
F. Berman, R. Wolski, S. Figueira, J. Schopf, G. Shao, Application-level scheduling on distributed heterogeneous networks, in: Proceedings of the ACM/IEEE Conference on Supercomputing, Pittsburgh, 1996. Google Scholar
F. Berman, G. Fox, T. Hey (Eds.), Grid Computing: Making the Global Infrastructure a Reality, Wiley Series in Communications Networking and Distributed Systems, Wiley, 2003. Google Scholar
V. Berstis, Fundamentals of grid computing. IBM Publication, http://www.redbooks.ibm.com/abstracts/redp3613.html, 2011 (accessed 26.04.11).Google Scholar
BOINCstats-Boinc combined credit overview, http://www.boincstats.com/stats/project_graph.php?pr=bo, 2011 (accessed 26.04.11).Google Scholar
R. Buyya, D. Abramson, S. Venugopal, The Grid Economy, in: Proceedings of the IEEE, 2005, pp. 698-714.Google ScholarCross Ref
R. Buyya, K. Bubendorfer (Eds.), Market Oriented Grid and Utility Computing, John Wiley & Sons, 2009. Google Scholar
A. Chervenak, et al., Giggle: a framework for constructing scalable replica location services, in: Proceedings of the 2002 ACM/IEEE Conference on Supercomputing, Baltimore, 16-22 November 2002. Google ScholarCross Ref
Dongarra, I. Fister, G. Fox, et al., Sourcebook of Parallel Computing, Morgan Kaufman Publishers, 2002. Google Scholar
L. Ferreira, et al., Introduction to Grid Computing with Globus, (http://www.redbooks.ibm.com/abstracts/sg246895.html?OPen) Google Scholar
L. Ferreira, et al., Grid Computing in Research and Education, (http://www.redbooks.ibm.com/abstracts/sg246649.html?OPen) Google Scholar
Folding@Home. (http://fah-web.stanford.edu/cgi-bin/main.py?qtype=ossrats), 2011, (accessed 7.03.2011).Google Scholar
I. Foster, C. Kasselman, Grid2: Blueprint for a New Computing Infrastructure, Morgan Kaufman Publishers, 2002. Google Scholar
I. Foster, C. Kesselman, S. Tuecke, The anatomy of the grid: enabling scalable virtual organizations, Int. J High. Perform. Comput. Appl. 15 (3) (2001) 200. Google ScholarDigital Library
I. Foster, Globus toolkit version 4: software for service-oriented systems, J. Comput. Sci. Technol. 21 (4) (2006) 513-520.Google Scholar
L. Francesco, et al., The many faces of the integration of instruments and the grid, Int. J. Web. Grid. Services 3 (3) (2007) 239-266. Google ScholarDigital Library
L. Gong, S.H. Sun, E.F. Watson, Performance modeling and prediction of non-dedicated network computing, IEEE. Trans. Comput., (2002). Google Scholar
G. Yuan, H. Jin, M. Li, N. Xiao, W. Li, Z. Wu, Y. Wu, Grid computing in China, J. Grid. Comput. 2 (2) (2004).Google Scholar
W. Hoschek, J. Jaen-Martinez, A. Samar, H. Stockinger, K. Stockinger, Data management in an international data grid project, in: Proceedings of the 1st IEEE/ACM International Workshop on Grid Computing (Grid 2000), Bangalore, India, 17 December 2000, pp. 77-90. Google ScholarCross Ref
K. Hwang, Z. Xu, Scalable Parallel Computing, McGraw-Hill, 1998. Google Scholar
K. Hwang, Y. Kwok, S. Song, M. Cai, Yu Chen, Y. Chen, DHT-based security infrastructure for trusted internet and grid computing, Int. J. Crit. Infrastructures 2 (4) (2006) 412-433.Google ScholarCross Ref
M.A. Iverson, F. Ozguner, L. Potter, Statistical prediction of task execution time through analytical benchmarking for scheduling in a heterogeneous environment, IEEE. Trans. Comput., (1999) 1374-1379. Google Scholar
L. Jiadao, R. Yahyapour, Negotiation model supporting co-allocation for grid scheduling, in: Proceedings of the 7th IEEE/ACM International Conference on Grid Computing, 2006, p. 8. Google Scholar
H. Jin, Challenges of grid computing, Advances in Web-Age Information Management. Lecture Notes in Computer Science, 3739 (2005) 25-31. Google ScholarDigital Library
M. Kalantari, M. Akbari, Fault-aware grid scheduling using performance prediction by workload modelling, J. Supercomput. 46 (1) (2008). Google ScholarDigital Library
C. Karnow, The grid: blueprint for a new computing infrastructure, Leonardo 32 (4) (1999) 331-332.Google ScholarCross Ref
K. Krauter, R. Buyya, M. Maheswaran, A taxonomy and survey of grid resource management systems for distributed computing, Softw. Pract. Exper. 32 (2) (2002) 135-164. Google ScholarDigital Library
R. Kwok, K. Hwang, S. Song, Selfish grids: game-theoretic modeling and NAS/PSA benchmark evaluation, IEEE Trans. Parallel. Distrib. Syst., (May) (2007). Google ScholarCross Ref
M. Li, M. Baker, The Grid: Core Technologies, Wiley, 2005, (http://coregridtechnologies.org/). Google Scholar
H. Li, Performance evaluation in grid computing: a modeling and prediction perspective, in: Seventh IEEE International Symposium on Cluster Computing and The Grid, (CCGrid 2007), May 2007, pp. 869-874. Google ScholarDigital Library
X. Lijuan, Z. Yanmin, L.M. Ni, Z. Xu, GridIS: an incentive-based grid scheduling, in: Proceedings of the 19th IEEE Int'l Parallel and Distributed Processing Symposium, 4-8 April 2005. Google Scholar
C. Lin, V. Varadharajan, Y. Wang, V. Pruthi. Enhancing grid security with trust management, in: Proc. of the 2004 IEEE International Conference on Services Computing, Washington, DC, 14 September 2004, pp. 303-310. Google ScholarDigital Library
J. Nash, Non-Cooperative Games, Ann. Math. Second Series 54 (2) (1951) 286-295.Google ScholarCross Ref
P. Plaszczak, R. Wellner, Grid Computing: The Savvy Manager's Guide, Kaufmann, 2006. Google Scholar
M. Poess, N. Raghunath, Larege-scale data warehouses on grid, http://www.vldb2005.org/program/papertue/p1055-poess.pdf, 2005.Google Scholar
J. Schopf, F. Berman, Performance prediction in production environments, in: 12th International Parallel Processing Symposium, Orlando, FL, April 1998, pp. 647-653. Google ScholarCross Ref
SETI@Home credir overview, (http://www.boincstats.com/stats/project_graph.php?pr=sah), (accessed 21.04.11).Google Scholar
H. Shen, K. Hwang, Locality-preserving clustering and discovery of resources in wide-area computational grids, IEEE. Trans. Comput. (accepted to appear 2011). Google Scholar
R. Smith, Grid computing: a brief technology analysis, CTO Network Library. (http://www.ctonet.org/documents/GridComputing_analysis.pdfGoogle Scholar
S. Song, K. Hwang, R. Zhou, Y.K. Kwok, Trusted P2P transactions with fuzzy reputation aggregation, IEEE. Internet. Comput. (November-December) (2005) 18-28. Google Scholar
S. Song, K. Hwang, Y.K. Kwok, Trusted grid computing with security binding and trust integration, J. Grid. Comput. 3 (1-2) (2005).Google ScholarCross Ref
S. Song, K. Hwang, Y. Kwok, Risk-tolerant heuristics and genetic algorithms for security-assured grid job scheduling, IEEE. Trans. Comput., (2006) 703-719. Google Scholar
Sun Microsystems, How Sun Grid Engine, enterprise edition works. White paper, www.sun.com/sofware/gridware/sgeee53/wp-sgeee.pdf, 2001.Google Scholar
I. Taylor, From P2P to Web Services and Grids, Springer-Verlag, London, 2005.Google Scholar
D. Thain, T. Tannenbaum, M. Livny, Distributed computing in practice: the condor experience, Concurrency. Comput. Pract. Exp., (2005) 323-356. Google Scholar
S. Venugopal, R. Buyya, K. Ramamohanarao, A taxonomy of data grids for distributed data sharing, management, and processing. ACM. Comput. Surv. 38 (1) (2006) 1-53. Google ScholarDigital Library
S. Venugopal, R. Buyya, L. Winton, A grid service broker for scheduling e-science applications on global data grids, Concurrency. Comput. Pract. Exp. 18 (6) (2006) 685-699. Google ScholarDigital Library
H. Wang, Z. Xu, Y. Gong, W. Li, Agora: grid community in Vega grid, in: Proceedings of the 2nd International Workshop on Grid and Cooperative Computing, Shanghai, China, 7 December, 2003, pp. 685-691.Google Scholar
V. Welch, et al., Security for grid services, in: Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing, June 22-24, 2003, pp. 48-57. Google ScholarDigital Library
Wikipedia, Grid Computing. http://een.wikipedia.org/wiki/Grid_computing, (accessed 26.04.11).Google Scholar
Y. Wu, S. Wu, H. Yu, C. Hu, CGSP: an extensible and reconfigurable grid framework, Lect. Notes. Comput. Sci. 3756 (2005) 292-300. Google ScholarDigital Library
Y. Wu, C. Hu, L. Zha, S. Wu, Grid middleware in China, Int. J. Web. Grid. Serv. 3 (4) (2007) 371-402. Google ScholarDigital Library
Y. Wu, K. Hwang, Y. Yuan, W. Zheng, Adaptive workload prediction of grid performance in confidence windows, IEEE Trans. Parallel. Distrib. Syst., (July) (2010). Google Scholar
Y.W. Wu, S. Wu, H.S. Yu, C.M. Hu, Introduction to ChinaGrid support platform, in: Proceedings of Parallel and Distributed Processing and Applications, 2005, pp. 232-240. Google Scholar
Z. Xu, W. Li, L. Zha, H. Yu, D. Liu, Vega: a computer systems approach to grid computing, J. Grid. Comput. 2 (2) (2004) 109-120.Google ScholarCross Ref
L. Yang, I. Foster, J.M. Schopf, Homeostatic and tendency-based CPU load predictions, in: International Parallel and Distributed Processing Symposium, 2003, pp. 42-50. Google ScholarCross Ref
X. Zhang, J. Schopf, Performance analysis of the globus toolkit monitoring and discovery service, MDS2, in: Proceedings of the Int'l Workshop on Middleware Performance, 2004, pp. 843-849.Google Scholar
W. Zheng, L. Liu, M. Hu, Y. Wu, L. Li, F. He, J. Tie, CGSV: an adaptable stream-integrated grid monitoring system, Network. Parallel. Comput. 3779 (2005) 22-31. Lecture Notes in Computer Science, Springer. Google ScholarDigital Library
S. Androutsellis, D. Spinellis, A survey of P2P content distribution technologies. ACM. Comput. Surv. (December) (2004). Google Scholar
L. Amaral, A. Scala, M. Barthelemy, M. Stanley, Classes of small-world networks. Natl. Acad. Sci. 97 (21) (2000).Google Scholar
S.A. Baset, H. Schulzrinne, An analysis of the Skype peer-to-peer Internet telephony protocol, in: Proceedings of IEEE INFOCOM, April 2006.Google ScholarCross Ref
R. Bindal, P. Cao, W. Chan, et al., Improving traffic locality in BitTorrent via biased neighbor selection, in: Proceedings of IEEE ICDCS, 2006. Google ScholarDigital Library
B. Bloom, Space/time tradeoffs in hash coding with allowable errors. Commun. ACM. 13 (7) (1970) 422-426. Google ScholarDigital Library
J. Buford, H. Yu, E. Lua, P2P Networking and Applications, Morgan Kaufmann, December 2008. Also www.p2pna.com. Google Scholar
M. Castro, P. Druschel, Y.C. Hu, A. Rowstron, Exploiting network proximity in distributed hash tables, in: Proceedings of the International Workshop on Future Directions in Distributed Computing, June 2002.Google Scholar
X. Cheng, J. Liu, NetTube: exploring social networks for peer-to-peer short video sharing, in: Proceedings of IEEE Infocom, March 2009.Google ScholarCross Ref
S. Chen, B. Shi, S. Chen, ACOM: any-source capacity-constrained overlay multicast in non-DHT P2P networks, in: IEEE Transactions on Parallel and Distributed Systems, September 2007, pp. 1188-1201. Google ScholarDigital Library
I. Clarke, O. Sandberg, B. Wiley, T.W. Hong, Freenet: a distributed anonymous information storage and retrieval system, in: ICSI Workshop on Design Issues in Anonymity and Unobservability, June 2000.Google Scholar
E. Cohen, S. Shenker, Replication strategies in unstructured peer-to-peer networks, in: ACM SIGCOMM, 2002. Google Scholar
A. Fiat, J. Saia, M. Young, Making chord robust to Byzantine attacks, in: Proceedings of the European Symposium on Algorithms (ESA), 2005. Google Scholar
A.J. Ganesh, A.M. Kermarrec, L. Massoulié, Peer-to-peer membership management for gossip-based protocols. IEEE. Trans. Computers. 52 (2) (2003) 139-149. Google ScholarDigital Library
P.B. Godfrey, S. Shenker, I. Stoica, Minimizing churn in distributed systems. in: Proceedings of ACM SIGCOMM, 2006. Google Scholar
S. Guha, N. Daswani, R. Jain, An experimental study of the Skype peer-to-peer VoIP system, in: Proceedings of the International Workshop on Peer-to-Peer Systems (IPTPS), February 2006.Google Scholar
K.P. Gummadi, R. Gummadi, S.D. Gribble, et al., The impact of DHT routing geometry on resilience and proximity, in: Proceedings of ACM SIGCOMM, 2003. Google ScholarCross Ref
M. Hefeeda, O. Saleh, Traffic modeling and proportional partial caching for peer-to-peer systems, in: IEEE/ACM Transactions on Networking, December 2008, pp. 1447-1460. Google ScholarDigital Library
Y. Huang, et al., Challenges, design and analysis of a large-scale P2P VOD system, in: Proceedings of ACM SIGCOMM 2008, Seattle, August 2008. Google ScholarDigital Library
K. Hwang, D. Li, Trusted cloud computing with secure resources and data coloring, IEEE. Inte. Comput. (September) (2010) 14-22. Google ScholarDigital Library
S. Kamvar, M. Schlosser, H. Garcia-Molina, The Eigentrust algorithm for reputation management in P2P networks, ACM WWW '03, Budapest, Hungary, 2003. Google ScholarDigital Library
A. Keromytis, V. Misra, D. Rubenstein, SOS: secure overlay services, in: Proceedings of ANM SIGCOMM' 02, Pittsburg, PA. August 2002. Google Scholar
J. Kleinberg, The small-world phenomenon: an algorithmic perspective, in: Proceedings 32nd ACM Symposium on Theory of Computing, Portland, OR. May 2000. Google ScholarDigital Library
J. Leitao, J. Pereira, L. Rodrigues, Epidemic broadcast trees, in: Proceedings of the 26th IEEE International Symposium on Reliable Distributed Systems, October 2007. Google ScholarDigital Library
Z. Li, G. Xie, K. Hwang, Z. Li, Churn-resilient protocol for massive data dissemination in P2P networks, in: IEEE Transactions on Parallel and Distributed Systems, accepted to appear 2011. Google ScholarDigital Library
Z. Li, G. Xie, Z. Li, Efficient and scalable consistency maintenance for heterogeneous peer-to-peer systems, in: IEEE Transactions on Parallel and Distributed Systems, December 2008, pp. 1695-1708. Google Scholar
Z. Li, G. Xie, Enhancing content distribution performance of locality-aware BitTorrent systems, in: Proceedings of IEEE Globecom, December 2010.Google Scholar
L. Liu, W. Shi, Trust and reputation management, in: IEEE Internet Computing, September 2010, pp. 10-13. (special issue).Google Scholar
Y. Liu, L. Xiao, X. Liu, L. M Ni, X. Zhang, Location awareness in unstructured peer-to-peer systems, in: IEEE Transactions on Parallel and Distributed Systems, February 2005, pp. 163-174. Google Scholar
J. Liu, S.G. Rao, B. Li, H. Zhang, Opportunities and challenges of peer-to-peer internet video broadcast, in: Proceedings of the IEEE Special Issue on Recent Advances in Distributed Multimedia Communications, Vol. 96 (1), 2008, pp. 11-24.Google Scholar
T. Locher, P. Moor, S. Schmid, R. Watenhofer, Free riding in BitTorrent is cheap, in: Proceedings of ACM HotNets, November 2006.Google Scholar
X. Lou, K. Hwang, Collusive piracy prevention in P2P content delivery networks, in: IEEE Transactions on Computers, Vol. 58, (7) 2009, pp. 970-983. Google ScholarDigital Library
B.T. Loo, R. Huebsch, I. Stoica, J. M. Hellerstein, The Case for a Hybrid P2P Search Infrastructure, 3rd International Workshop on Peer-to-Peer Systems, February 2004. Google Scholar
Q. Lv, P. Cao, E. Cohen, K. Li, S. Shenker, Search and replication in unstructured peer-to-peer networks, in: Proceedings of the ACM International Conference on Supercomputing, June 2002. Google ScholarCross Ref
B. Maniymaran, M. Bertier, A.-M. Kermarrec, Build one, get one free: leveraging the coexistence of multiple P2P overlay networks, in: Proceedings of the International Conference on Distributed Computing Systems, Toronto, June 2007. Google ScholarDigital Library
P. Maymounkov, D. Mazières, Kademlia: a peer-to-peer information system based on the XOR metric, in: Proceedings of the International Workshop on Peer-to-Peer Systems (IPTPS), March 2002. Google ScholarCross Ref
N. Magharei, R. Rejaie, Y. Guo, Mesh or multiple-tree: a comparative study of live P2P streaming approaches, in: Proceedings of IEEE INFOCOM, Alaska, May 2007.Google ScholarDigital Library
G. Pallis, A. Vakali, Insight and perspectives for content delivery networks, Commun. ACM 49 (1) (2006) 101-106. Google ScholarDigital Library
K. Ross, D. Rubenstein, Peer-to-peer systems, in: IEEE Infocom, Hong Kong, 2004, (Tutorial slides).Google Scholar
A. Rowstron, P. Druschel, Pastry: scalable, decentralized object location and routing for large-scale peer-to-peer systems, in: Proceedings of the IFIP/ACM International Conference on Distributed Systems Platforms (Middleware), Heidelberg, Germany, November 2001, pp. 329-350. Google ScholarCross Ref
S. Ratnasamy, P. Francis, M. Handley, R. Karp, A scalable content-addressable network, in: Proceedings of ACM SIGCOMM, August 2001. Google ScholarDigital Library
S. Saroiu, P. Gummadi, S. Gribble, A measurement study of peer-to-peer file sharing systems, in: Multimedia Computing and Networking (MMCN '02), January 2002.Google Scholar
H. Shen, C. Xu, Locality-aware and churn-resilient load balancing algorithms in structured peer-to-peer networks, in: IEEE Transactions on Parallel and Distributed Systems, Vol. 18 (6), June 2007, pp. 849-862. Google ScholarDigital Library
S. Song, K. Hwang, R Zhou, Y.K. Kwok, Trusted P2P transactions with fuzzy reputation aggregation, in: IEEE Internet Computing, November-December 2005, pp. 18-28. Google Scholar
M. Steiner, T. En-Najjary, E. Biersack, Long term study of peer behavior in the KAD DHT, in: IEEE/ ACM Transactions on Networking, Vol. 17 (6) 2009. Google Scholar
I. Stoica, R. Morris, D. Liben-Nowell, et al., Chord: a scalable peer-to-peer lookup service for Internet applications, in: IEEE/ACM Transactions on Networking, Vol. 11 (1) February 2003, pp. 17-32. Google ScholarDigital Library
K. Spripanidkulchai, B. Maggs, H. Zhang, Efficient content location using interest-based locality in peer-to-peer systems, in: Proceedings of IEEE INFOCOM, 2003.Google Scholar
C. Tang, R.N. Chang, C. Ward, GoCast: gossip-enhanced overlay multicast for fast and dependable group communication, in: Proceedings of the International Conference on Dependable Systems and Networks, Yokohama, Japan, June 2005, pp. 140-149. Google Scholar
V. Venkataraman, K. Yoshida, P. Francis, Chunkyspread: heterogeneous unstructured tree-based peer to peer multicast, in: 14th IEEE International Conference on Network Protocols, November 2006, pp. 2-11. Google ScholarDigital Library
Y. Wang, J. Vassileva, Trust and reputation model in peer-to-peer networks, in: Third International Conference on Peer-to-Peer Computing, August 2003. Google Scholar
Wikipedia, Peer to Peer. http://en.wikipedia.org/wiki/Peer-to-peer, 2010 (accessed 14.08.2010).Google Scholar
R.H. Wouhaybi, A.T. Campbell, Phoenix: supporting resilient low-diameter peer-to-peer topologies, in: IEEE INFOCOM, 2004.Google ScholarCross Ref
L. Xiao, Y. Liu, L.M. Ni, Improving unstructured peer-to-peer systems by adaptive connection establishment, in: IEEE Transactions on Computers, Vol. 54 (9), September 2005, pp. 1091-1103. Google ScholarDigital Library
L. Xiong, L. Liu, Peertrust: supporting reputation-based trust for peer-to-peer electronic communities, in: IEEE Transactions on Knowledge and Data Engineering, Vol. 16 (7), 2004, pp. 843-857. Google ScholarDigital Library
Z. Xu, C. Tang, Z. Zhang, Building topology-aware overlays using global soft-state, in: Proceedings on the International Conference on Distributed Computing Systems, 2003. Google Scholar
M. Yang, Y. Dai, X. Li, Bring reputation system to social network in the maze P2P file-sharing system, in: IEEE 2006 International Symposium on Collaborative Technologies and Systems (CTS 2006), Las Vegas, 14-17 May 2006. Google Scholar
Z. Zhang, S. Chen, Y. Ling, R. Chow, Capacity-aware multicast algorithms in heterogeneous overlay networks, in: IEEE Transactions on Parallel and Distributed Systems, February 2006, pp. 135-147. Google ScholarDigital Library
R. Zhou, K. Hwang, PowerTrust for fast reputation aggregation in peer-to-peer networks, in: IEEE Transactions on Parallel and Distributed Systems, April 2007, pp. 460-473. Google ScholarDigital Library
R. Zhou, K. Hwang, M. Cai, GossipTrust for fast reputation aggregation in peer-to-peer networks, in: IEEE Transactions on Knowledge and Data Engineering, September 2008, pp. 1282-1295. Google ScholarCross Ref
Z. Zhou, Z. Li, G. Xie, ACNS: Adaptive complementary neighbor selection in BitTorrent-like applications, in: Proceedings of IEEE ICC 2009, Germany, 2009. Google ScholarCross Ref
Y. Zhu, Y. Hu, Enhancing search performance on Gnutella-Like P2P systems, in: IEEE Transactions on Parallel and Distributed Systems, Vol. 17 (12), December 2006, pp. 1482-1495. Google ScholarDigital Library
M. Armbrust, A. Fox, R. Griffith, et al., Above the Clouds: A Berkeley View of Cloud Computing, Technical Report No. UCB/EECS-2009-28, University of California at Berkley, 10 February 2009.Google Scholar
C. Bardaki, P. Kourouthanassis, RFID-integrated retail supply chain services: Lessons learnt from the SMART project, in: Proceedings of the Mediterranean Conference on Information Systems (MCIS 2009), Athens, Greece.Google Scholar
M. Barrenechea, SGI CEO. HPC Cloud-Cyclone. www.sgi.com/cyclone, 2010.Google Scholar
J. Bishop, Understanding and Facilitating the Development of Social Networks in Online Dating Communities: A Case Study and Model. www.jonathanbishop.com/Library/Documents/EN/docSNCEDS_Ch15 .pdf, 2008.Google Scholar
R. Bryant, Data Intensive Supercomputing: The Case for DISC, Technical Report, CMU CS-07-128, http://www.cs.cmu.edu/~bryant, 2007.Google Scholar
J. Brodkin, Ten Cloud Computing Companies to Watch. Network World. www.cio.com/article/print/ 492885, 2010.Google Scholar
S. Buchegger, A. Datta, A case for P2P infrastructure for social networks: Opportunities, challenges, in: Sixth International Conference on Wireless on-Demand Network Systems and Services (WONS 2009). Google ScholarDigital Library
R. Buyya, J. Broberg, A. Goscinski (Eds.), Cloud Computing: Principles and Paradigms, Wiley Press, New York, 2011. Google Scholar
R. Buyya, C. Yeo, S. Venugopal, Market-oriented cloud computing: Vision, hype, and reality for delivering IT services as computing utilities, in: 10th IEEE International Conference on High Performance Computing and Communications, September 2008. Google ScholarDigital Library
P. Carrington, et al., (Eds.), Modelsand Methods in Social Network Analysis, Cambridge University Press, 2005.Google Scholar
CERN VM download. http://rbuilder.cern.ch/project/cernvm/build?id=81, 2010.Google Scholar
K. Chen, K. Hwang, G. Chen, Heuristic discovery of role-based trust chains in P2P networks, IEEE Trans. Parallel Distrib. Syst. (2009) 83-96. Google Scholar
Condor Cloud Computing. www.cs.wisc.edu/condor/description.html, 2010.Google Scholar
J. Dean, Handling Large Datasets at Google: Current Systems and Future Directions, Invited Talk at HSF Panel. http://labs.google.com/people/jeff, 2008.Google Scholar
E. Deelman, G. Singh, M. Livny, B. Berriman, J. Good, The cost of doing science on the cloud: The Montage example, in: Proc. of ACM/IEEE Conf. on Supercomputing, IEEE Press, Austin, TX, 2008, pp. 1-12. Google Scholar
M. Demirbas, M.A. Bayir, C.G. Akcora, Y.S. Yilmaz, H. Ferhatosmanoglu, Crowd-sourced sensing and collaboration using Twitter, in: IEEE International Symposium on World of Wireless Mobile and Multimedia Networks (WoWMoM), Montreal, 14-17 June 2010, pp. 1-9. Google Scholar
Distributed Robotics Garden, MIT. http://people.csail.mit.edu/nikolaus/drg/, 2010.Google Scholar
V. Dixit, Cloud Mashup: Agility and Scalability, EE 657 Final Project Report, Univ. of S. Calif., May 2010.Google Scholar
J. Ekanayake, X. Qiu, T. Gunarathne, S. Beason, G. Fox, High performance parallel computing with clouds and cloud technologies, in: Cloud Computing and Software Services: Theory and Techniques, CRC Press (Taylor and Francis), 2010, p. 30.Google ScholarCross Ref
J. Ekanayake, A.S. Balkir, T. Gunarathne, et al., DryadLINQ for scientific analyses, in: Fifth IEEE International Conference on eScience, Oxford, England, 2009. Google ScholarDigital Library
J. Ekanayake, H. Li, B. Zhang, et al., Twister: A runtime for iterative MapReduce, in: Proceedings of the First Int'l Workshop on MapReduce and Its Applications, ACM HPDC, 20-25 June 2010, Chicago. Google Scholar
J. Ekanayake, T. Gunarathne, J. Qiu, Cloud technologies for bioinformatics applications, in: IEEE Transactions on Parallel and Distributed Systems, accepted to appear, http://grids.ucs.indiana.edu/ptliupages/publications/BioCloud_TPDS_Journal_Jan4_2010.pdf, 2011. Google Scholar
S. Farnham, The Facebook Application Ecosystem, An O'Reilly Radar Report, 2008.Google Scholar
Q. Feng, K. Hwang, Y. Dai, Rainbow Product Ranking for Upgrading e-Commerce, IEEE Internet Comput. 13 (5) (2009) 72-80. Google ScholarDigital Library
D.G. Feitelson, Workload Modeling for Computer Systems Performance Evaluation, Draft Version 0.7, Hebrew University of Jerusalem, 2006.Google Scholar
P. Fong, M. Anwar, Z. Zhao, A privacy preservation model for Facebook-style social network systems, in: European Symposium on Research in Computer Security (ESORICS 2009), 21-23 September 2009. Google ScholarCross Ref
F. Fovet, Impact of the use of Facebook amongst students of high school age with social, emotional and behavioural difficulties (SEBD), in: IEEE 39th Frontiers in Education Conference, 2009. Google ScholarDigital Library
G. Fox, S. Bae, J. Ekanayake, X. Qiu, H. Yuan, Parallel data mining from multicore to cloudy grids, in: High Speed and Large Scale Scientific Computing, IOS Press, Amsterdam, 2009.Google Scholar
L. Freeman, The Development of Social Network Analysis, Empirical Press, Vancouver, 2006.Google Scholar
FutureGrid Cyberinfrastructure to allow testing of innovative systems and applications, Home page. www .futuregrid.org, (accessed 13.11.10).Google Scholar
S.L. Garfinkel, An evaluation of Amazon's grid computing services: EC2, S3 and SQS, in: Center for Research on Computation and Society, Harvard University, Technical Report, 2007.Google Scholar
S. Garfinkel, Commodity grid computing with Amazon's S3 and EC2, Login 32 (1) (2007) 7-13.Google Scholar
L. Gong, S.H. Sun, E.F. Watson, Performance modeling and prediction of non-dedicated network computing, IEEE Trans. Computers 51 (9) (2002) 1041-1055. Google ScholarDigital Library
A. Greenberg, J. Hamilton, D.A. Maltz, P. Patel, The cost of a cloud: Research problems in data center networks, in: SIGCOMM Computer Communication Review, Vol. 39, No. 1, pp. 68-73, 2008, http://doi .acm.org/10.1145/1496091.1496103. Google ScholarDigital Library
Grid'5000 and ALADDIN-G5K: An infrastructure distributed in 9 sites around France, for research in large-scale parallel and distributed systems. https://www.grid5000.fr/mediawiki/index.php/Grid5000:Home, (accessed 20.11.10).Google Scholar
R. Grossman, Y. Gu, M. Sabala, et al., The open cloud testbed: Supporting open source cloud computing systems based on large scale high performance, in: A. Doulamis, et al., (Eds.), DynamicNetwork Services, Springer, Berlin Heidelberg, 2010, pp. 89-97.Google Scholar
R. Grossman, Y. Gu, J. Mambretti, et al., An overview of the open science data cloud, in: Proc. of the 19th ACM Int'l Symp. on High Performance Distributed Computing, Chicago, 2010, pp. 377-384. Google ScholarDigital Library
T. Gunarathne, T.L. Wu, J. Qiu, G. Fox, Cloud Computing Paradigms for Pleasingly Parallel Biomedical Applications, in: Proceedings of the Emerging Computational Methods for the Life Sciences Workshop of ACM HPDC 2010 Conference, Chicago, 20-25 June 2010. Google Scholar
C. Hoffa, et al., On the use of cloud computing for scientific workflows, in: IEEE Fourth International Conference on eScience, December 2008. Google ScholarDigital Library
J. Hopcroft, Computer science theory to support research in the information age, in: Distinguished Lecture, University of Southern California, 6 April 2010.Google Scholar
K. Hwang, Z. Xu, Scalable Parallel Computing: Technology, Architecture and Programmability, McGraw-Hill Book Co., New York, 1998. Google Scholar
K. Hwang, D. Li, Trusted cloud computing with secure resources and data coloring, IEEE Internet Comput. (September) (2010) 14-22. Google ScholarDigital Library
K. Keahey, M. Tsugawa, A. Matsunaga, J. Fortes, Sky computing, IEEE Internet Comput. 13 (2009) 43-51, doi:http://doi.ieeecomputersociety.org/10.1109/MIC.2009.94; www.nimbusproject.org/files/Sky_Computing.pdf. Google ScholarDigital Library
J. Kleinberg, Algorithmic Perspectives on Large-Scale Social Network Data, Cornell University, 2008.Google Scholar
G. Kortuem, F. Kawsar, D. Fitton, V. Sundramoorthy, Smart objects as building blocks for the Internet of things, IEEE Internet Comput. 14 (1) (2010) 44-51. Google ScholarDigital Library
R. Kumar, J. Novak, A. Tomkins, Structure and evolution of online social networks, in: The 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2006. Google ScholarDigital Library
E.A. Lee, Cyber physical systems: Design challenges, in: 11th IEEE International Symposium on Object Oriented Real-Time Distributed Computing, 5-7 May 2008, pp. 363-369. Google ScholarDigital Library
A. Langville, C. Meyer, Google's PageRank and Beyond: The Science of Search Engine Rankings, Princeton University Press, Princeton, NJ, 2006. Google ScholarDigital Library
J. Leskovec, K. Langt, A. Dagupta, M. Mahoney, Statistical properties of community structure in large social and information networks, in: International World Wide Web Conference, (WWW), 2008. Google Scholar
H. Li, Performance evaluation in grid computing: A modeling and prediction perspective, in: Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2007), May 2007, pp. 869-874. Google ScholarDigital Library
Z.Y. Li, G. Xie, K. Hwang, Z.C. Li, Proximity-Aware overlay network for fast and churn resilient data dissemination, in: IEEE Transactions on Parallel and Distributed Systems, Accepted to appear 2011.Google ScholarDigital Library
D. Linthicum, Cloud Computing and SOA Convergence in Your Enterprise: A Step-by-Step Guide, Addison Wesley Professional, 2009. Google Scholar
B.A. Lloyd, Professional networking on the Internet, in: Pulp and Paper Industry Technical Conference, Birmingham, AL, 2009, pp. 62-66.Google ScholarCross Ref
X. Lou, K. Hwang, Collusive Piracy Prevention in P2P Content Delivery Networks, IEEE Trans. Computers 58 (July) (2009) 970-983. Google ScholarDigital Library
X. Lou, K. Hwang, Y. Hu, Accountable file indexing against poisoning DDoS attacks in P2P networks, in: IEEE Globecom, Honolulu, 3 November 2009. Google Scholar
Magellan: A cloud for science at Argonne. http://magellan.alcf.anl.gov/, (accessed 15.11.10).Google Scholar
L. Mei, W. Chan, T. Tse, A tale of clouds: Paradigm comparisons and some thoughts on research issues, in: IEEE Asia-Pacific Services Computing Conference, December 2008. Google ScholarDigital Library
A. Mislove, M. Marcon, K.P. Gummadi, P. Druschel, B. Bhattacharjee, Measurement and analysis of online social networks, in: The 7th ACM SIGCOMM Conference on Internet Measurement, October 2007. Google Scholar
J. Napper, P. Bientinesi, Can cloud computing reach the top500? in: Proceedings of the Combined Workshops on Unconventional High Performance Computing Workshop Plus Memory Access Workshop, ACM, Ischia, Italy, 2009, pp. 17-20. Google ScholarDigital Library
Nimbus Cloud Computing. http://workspace.globus.org/, 2010.Google Scholar
W. Norman, M. Paton, T. de Aragao, et al., Optimizing utility in cloud computing through autonomic workload execution, in: IEEE Computer Society Technical Committee on Data Engineering, 2009.Google Scholar
D. Nurmi, R. Wolski, C. Grzegorczyk, et al., Eucalyptus: A technical report on an elastic utility computing architecture linking your programs to useful systems, UCSB, Santa Barbara, Technical Report, 2008.Google Scholar
C. Olston, B. Reed, B.U. Srivastava, et al., Pig Latin: A not-so-foreign language for data processing, in: Proceedings of the 2008 ACM SIGMOD Int'l Conf. on Management of Data, Vancouver, 9-12 June 2008. Google ScholarDigital Library
Open Cirrus, Welcome to Open Cirrus, the HP/Intel/Yahoo! Open Cloud Computing Research Testbed. https://opencirrus.org/, (accessed 20.11.10).Google Scholar
M. Palankar, A. Onibokun, A. Iamnitchi, M. Ripeanu, Amazon S3 for science grids: A viable solution? Computer Science and Engineering, University of South Florida, Technical Report, 2007.Google Scholar
A. Passant, T. Hastrup, U. Bojars, J. Breslin, Microblogging: A semantic web and distributed approach, in: 4th Workshop on Scripting for the Semantic Web in conjunction with ESWC 2008.Google Scholar
J. Qiu, T. Gunarathne, J. Ekanayake, et al., Hybrid cloud and cluster computing paradigms for life science applications, in: 11th Annual Bioinformatics Open Source Conference (BOSC 2010), Boston, 9-10 July 2010.Google ScholarCross Ref
J. Qiu, T. Ekanayake, T. Gunarathne, et al., Data Intensive Computing for Bioinformatics. http://grids.ucs .indiana.edu/ptliupages/publications/DataIntensiveComputing_BookChapter.pdf, 29 December 2009.Google Scholar
D. Reed, Clouds, clusters and ManyCore: The revolution ahead, in: IEEE International Conference on Cluster Computing, 29 September-1 October 2008.Google Scholar
J. Rittinghouse, J. Ransome, Cloud Computing: Implementation, Management and Security, CRC Publisher, 2010. Google Scholar
B. Rochwerger, D. Breitgand, E. Levy, et al., The Reservoir Model and Architecture for Open Federated Cloud Computing, IBM Syst. J. (2008). Google Scholar
V. Sanhu, The CERN Virtual Machine and Cloud Computing, B.S. Thesis at the Dept. of Physics, University of Victoria, Canada, 29 January 2010.Google Scholar
G. Santucci, The Internet of Things: Between the Revolution of the Internet and the Metamorphosis of Objects. http://ec.europa.eu/information_society/policy/rfid/documents/iotrevolution.pdf, 2010.Google Scholar
M. Satyanarayanan, V. Bahl, R. Caceres, N. Davies, The case for VM-based cloudlets in mobile computing, IEEE Pervasive Comput. 8 (4) (2009) 14-23. Google ScholarDigital Library
J. Schopf, F. Berman, Performance prediction in production environments, in: 12th International Parallel Processing Symposium, Orlando, FL, April 1998, pp. 647-653. Google ScholarCross Ref
Science Clouds: Informal group of small clouds made available by various institutions on a voluntary basis. http://scienceclouds.org/, (accessed November 2010).Google Scholar
H. Song, Exploring Facebook and Twitter Technologies for P2P Social Networking, in: EE 657 Final Project Report, University of Southern California, May 2010.Google Scholar
H. Sundmaeker, P. Guillemin, P. Friess, S. Woelfflé, Vision and Challenges for Realising the Internet of Things, European Union, March 2010.Google Scholar
Venus-C, Virtual Multidisciplinary Environmemnts Using Cloud Infrastructure. www.venus-c.eu/Pages/Home.aspx, (accessed November 2010).Google Scholar
E. Walker, Benchmarking Amazon EC2 for high-performance scientific computing, Login 33 (5) (2008) 18-23.Google Scholar
E. Welbourne, L. Battle, G. Cole, et al., Building the Internet of things using RFID: the RFID ecosystem experience, IEEE Internet Comput. 13 (3) (2009) 48-55. Google ScholarDigital Library
S. Wasserman, K. Faust, Social Networks Analysis: Methods and Applications, Cambridge University Press, Cambridge, 1994.Google Scholar
D. Watts, Small Worlds: The Dynamics of Networks between Order and Randomness, Princeton University Press, Princeton, 2003. Google ScholarDigital Library
M. Weng, A Multimedia Social Networking Community for Mobile Devices, Tisch School of The Arts, New York University, 2007.Google Scholar
Wikipedia, Cyber-physical systems. http://en.wikipedia.org/wiki/Cyber-physical_system, 2010.Google Scholar
Wikipedia, Social Network. http://en.wikipedia.org/wiki/Social_network, 2010.Google Scholar
Wikipedia, Facebook. http://en.wikipedia.org/wiki/Facebook, March 3, 2011.Google Scholar
Wikipedia, Mashup (web app hybrid). http://en.wikipedia.org/wiki/Mashup_%28web_application_hybrid%, 29 November 2010.Google Scholar
Y. Wu, K. Hwang, Y. Yuan, C. Wu, Adaptive workload prediction of grid performance in confidence windows, IEEE Trans. Parallel Distrib. Syst. 21 (July) (2010) 925-938. Google Scholar
Z. Xu, K. Hwang, Early prediction of MPP performance: SP2, T3D, and paragon experiences, J. Parallel Comput. 22 (7) (1996) 917-942. Google ScholarDigital Library
L. Yan, Y. Zhang, L.T. Yang, H. Ning, The Internet of Things: From RFID to the Next-Generation Pervasive Networked Systems, Auerbach Publications, 2008. Google ScholarCross Ref
B. Yan, G. Huang, Supply chain information transmission based on RFID and Internet of things, in: International Colloquium on Computing, Communication, Control, and Management (CCCM 2009) Vol. 4, 2009, pp. 166-169.Google Scholar
M. Yigitbasi, A. Iosup, D. Epema, C-Meter: a framework for performance analysis of computing clouds, in: International Workshop on Cloud Computing, May 2009.Google Scholar
B.J. Zhang, Y. Ruan, T.L. Wu, J. Qiu, A. Hughes, G. Fox, Applying twister to scientific applications, in: International Conference on Cloud Computing (CloudCom 2010), http://grids.ucs.indiana.edu/ptliupages/publications/PID1510523.pdf, 2010. Google Scholar

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Kai Hwang
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Index Terms

Distributed and Cloud Computing: From Parallel Processing to the Internet of Things

Reviews

Reviewer: George Dimitoglou

If you were to ask ten people in computer science to define the term "distributed computing," you would likely receive ten different, yet correct, answers. Clearly there are no data or surveys to support this claim, but it is probably true and indicative of the breadth of this area of computing. So what is distributed computing__?__ Is it Internet computing__?__ Is it parallel computing or cloud computing__?__ Is it grid computing or Web services or peer-to-peer computing__?__ Well, it is all of the above and more, and this book manages to provide a comprehensive overview of the state of distributed computing today. The book is organized in three parts: "Systems Modelling, Clustering and Virtualization"; "Computing Clouds, Service-Oriented Architecture and Programming"; and "Grids, Peer-to-Peer and the Future of the Internet." Comprising three chapters, the first part introduces various distributed computing platforms and environments. It covers the gamut from network-based systems and cloud and clustered computing to virtual machines (VMs), grids, graphics processing units (GPUs), and massively parallel processors. The second part focuses on the principles and enabling technologies of cloud computing and service-oriented architectures (SOAs). It also contains a chapter dealing with the software development aspects in cloud environments, covering several programming paradigms (for example, MapReduce, Dryad, Sawall, and Pig Latin) and contemporary cloud platforms such as Google's App Engine, Amazon's EC2, and Microsoft's Azure. The third and last part of the book covers grid and peer-to-peer networks, and showcases existing clouds developed by industry and government organizations (for example, IBM, SGI, NASA, CERN). The book provides broad coverage of everything one needs to know about the field, striking a good balance between details that do not overwhelm and the basic principles. The authors provide many figures to support and illustrate the material. It is readable, coherent, and well structured and would be useful as a textbook for a primer in distributed systems for upper-level undergraduates or first-year graduate students. It would be equally appropriate for practitioners involved in hot contemporary information technology (IT) areas such as virtualization and cloud computing. Any professional in almost any capacity, from software developers to IT architects and chief information officers (CIOs), could benefit from reading the book to understand how things work or by having it as a reference. Besides explaining and contextualizing how distributed systems work, the book's coverage of numerous commercial platforms and technologies would serve as a useful resource to professionals engaged in deploying or planning modern distributed systems. For some, the strengths of the book may also be its weaknesses. In their attempt to be comprehensive, the authors couldn't cover all of the topics in depth. However, each chapter contains references to external sources (that is, scholarly papers and books) that could be very useful to help guide anyone interested in getting more information on a specific subject. The inclusion of current technologies and platforms may be attractive to practitioners and certainly increases the timeliness of the material, but it may also render this edition of the text obsolete within a few years. Having said that, I think it is interesting to see just from the mere arrangement of the chapters how distributed computing topics have evolved: the ruling platforms of the late 1990s and early 2000s-peer-to-peer networks and grid computing-have now taken a back seat to virtualization and cloud computing. Despite these quibbles, I find the book an excellent resource. It is well organized, and it contains extensive bibliographic notes at the end of each chapter along with appropriate problems and exercises that reinforce the material. Overall, this is perhaps the most comprehensive, timely, and well-written book in distributed computing available today. Online Computing Reviews Service

Reviewer: David Bruce Henderson

Distributed and cloud computing are receiving significant popular attention. While there is a great deal of marketing fervor and hype associated with the topic, it is undoubtedly one of the most important aspects of information technology today. There are literally dozens of books available on the subject, but this one differs in that it is designed primarily as a textbook, covering the design and application of distributed and cloud systems. The book is easy to navigate, and considerable effort appears to have been put into the format and layout. A detailed table of contents and thorough index allow for easy use as a reference, and appropriate diagrams and tables are employed throughout. The book is divided into three parts, each beginning with a brief summary. Each chapter begins with a chapter outline and ends with a set of problems (with solutions) for students and references. Part 1 starts with an introductory chapter on the changes in computing over the past three decades. Scalable computing, network-based systems, modeling, and distributed and cloud computing performance are covered. Two chapters then provide detailed coverage of clustering, parallel computing technologies, and virtual machines, particularly as deployed in data centers. Part 2 looks at cloud computing. Various cloud platforms, including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS), are covered. Chapters are devoted to cloud platform architecture in virtualized data center environments, service-oriented architectures for distributed computing, and distributed software programming environments. The topics discussed in each chapter are supported with detailed real-world examples. Part 3, the last part, examines future trends in distributed computing. One chapter covers the design, the platform, middleware, standards, and resource management in grid computing systems. Peer-to-peer (P2) computing and overlay networks are then discussed. In the last chapter, future trends in cloud and Internet computing are covered, along with an examination of some existing public and private cloud examples. The authors provide good general coverage of the technologies behind distributed and cloud computing. The writing style is quite consistent across the multiple contributors. Although there are many other titles on the subject, this book provides up-to-date general coverage and is laid out so as to be useful as a textbook. The thorough index and good table of contents-particularly the "distributed" tables of contents at the beginning of each chapter-also make it useful as a reference book. Online Computing Reviews Service

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