survey

A Survey of Cloudlet-Based Mobile Augmentation Approaches for Resource Optimization

Authors:

M. Ziad Nayyer,

Syed Asad HussainAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 51, Issue 5

Article No.: 107, Pages 1 - 28

https://doi.org/10.1145/3241738

Published: 19 November 2018 Publication History

Abstract

Mobile devices (MDs) face resource scarcity challenges owing to limited energy and computational resources. Mobile cloud computing (MCC) offers a resource-rich environment to MDs for offloading compute-intensive tasks encountering resource scarcity challenges. However, users are unable to exploit its full potential owing to challenges of distance, limited bandwidth, and seamless connectivity between the remote cloud (RC) and MDs in the conventional MCC model. The cloudlet-based solution is widely used to address these challenges. The response of the cloudlet-based solution is faster than the conventional mobile cloud-computing model, rendering it suitable for the Internet of Things (IoT) and Smart Cities (SC). However, with the increase in devices and workloads, the cloudlet-based solution has to deal with resource-scarcity challenges, thus, forwarding the requests to remote clouds. This study has been carried out to provide an insight into existing cloudlet-based mobile augmentation (CtMA) approaches and highlights the underlying limitations for resource optimization. Furthermore, numerous performance parameters have been identified and their detailed comparative analysis has been used to quantify the efficiency of CtMA approaches.

References

[1]

H. Allam, N. Nassiri, A. Rajan, and J. Ahmad. 2017. A critical overview of latest challenges and solutions of Mobile Cloud Computing. In Proceedings of the Second International Conference on Fog and Mobile Edge Computing (FMEC’17). 225--229.

[2]

M. Satyanarayanan. 2017. The emergence of edge computing. Computer 50, 1, 30--39.

Digital Library

[3]

N. Abbas, Y. Zhang, A. Taherkordi, and T. Skeie. 2018. Mobile edge computing: A survey. IEEE Internet of Things Journal 5, 1, 450--465.

[4]

Z. Pang, L. Sun, Z. Wang, E. Tian, and S. Yang. 2015. A survey of cloudlet based mobile computing. In Proceedings of the International Conference on Cloud Computing and Big Data (CCBD’15). 268--275.

Digital Library

[5]

R. Mahmud, R. Kotagiri, and R. Buyya. 2018. Fog computing: A taxonomy, survey and future directions. In Internet of Everything. Springer, 103--130.

[6]

K. Dolui and S. K. Datta. 2017. Comparison of edge computing implementations: Fog computing. Cloudlet and Mobile Edge Computing. In Global Internet of Things Summit (GIoTS’17). 1--6.

[7]

P. Mach and Z. Becvar. 2017. Mobile edge computing: A survey on architecture and computation offloading. IEEE Communications Surveys 8 Tutorials 19, 3, 1628--1656.

[8]

K. Bilal, O. Khalid, A. Erbad, and S. U. Khan. 2018. Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers. Computer Networks 130, 94--120.

[9]

S. Yi, C. Li, and Q. Li. 2015. A survey of fog computing: Concepts, applications and issues. In Proceedings of the 2015 Workshop on Mobile Big Data. 37--42.

Digital Library

[10]

P. Mell and T. Grance. 2009. The NIST definition of cloud computing. National Institute of Standards and Technology, Vol. 53. 50.

[11]

M. R. Rahimi, J. Ren, C. H. Liu, A. V. Vasilakos, and N. Venkatasubramanian. 2014. Mobile cloud computing: A survey, state of art and future directions. Mobile Networks and Applications 19, 2, 133--143.

Digital Library

[12]

S. Abolfazli, Z. Sanaei, E. Ahmed, A. Gani, and R. Buyya. 2014. Cloud-based augmentation for mobile devices: motivation, taxonomies, and open challenges. IEEE Communications Surveys 8 Tutorials 16, 1, 337--368.

[13]

M. Satyanarayanan. 2015. A brief history of cloud offload: A personal journey from odyssey through cyber foraging to cloudlets. GetMobile: Mobile Computing and Communications 18, 4, 19--23.

Digital Library

[14]

R. Buyya, C. S. Yeo, and S. Venugopal. 2008. 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’08). 5--13.

Digital Library

[15]

M. T. Desai, R. Patel, P. Patel, T. Desai, R. Patel, and P. Patel. 2016. Cloud computing in education sector. International Journal 2, 191--194.

[16]

P. P. Parikh, M. G. Kanabar, and T. S. Sidhu. 2010. Opportunities and challenges of wireless communication technologies for smart grid applications. In IEEE Power and Energy Society General Meeting. 1--7.

[17]

E. Ahmed, A. Gani, M. K. Khan, R. Buyya, and S. U. Khan. 2015. Seamless application execution in mobile cloud computing: Motivation, taxonomy, and open challenges. Journal of Network and Computer Applications 52, 154--172.

Digital Library

[18]

N. Aminzadeh, Z. Sanaei, and S. H. Ab Hamid. 2015. Mobile storage augmentation in mobile cloud computing: Taxonomy, approaches, and open issues. Simulation Modelling Practice and Theory 50, 96--108.

[19]

S. Distefano, F. Longo, and M. Scarpa. 2015. QoS assessment of mobile crowdsensing services. Journal of Grid Computing 13, 4, 629--650.

Digital Library

[20]

M. Othman, S. A. Madani, and S. U. Khan. 2014. A survey of mobile cloud computing application models. IEEE Communications Surveys 8 Tutorials 16, 1, 393--413.

[21]

M. Othman, A. N. Khan, S. A. Abid, and S. A. Madani. 2015. MobiByte: An application development model for mobile cloud computing. Journal of Grid Computing 13, 4, 605--628.

Digital Library

[22]

H. Qi and A. Gani. 2012. Research on mobile cloud computing: Review, trend and perspectives. In Proceedings of the Second International Conference on Digital Information and Communication Technology and It’s Applications (DICTAP’12). 195--202.

[23]

A. Mohammad and L. Chunlin. 2016. Cloud-based mobile augmentation in mobile cloud computing. International Journal of Future Generation Communication and Networking 9, 8, 65--76.

[24]

P. Patil, A. Hakiri, and A. Gokhale. 2016. Cyber foraging and offloading framework for Internet of Things. In Proceedings of the IEEE 40th Annual Conference on Computer Software and Applications (COMPSAC’16). 359--368.

[25]

K. Gai, M. Qiu, H. Zhao, L. Tao, and Z. Zong. 2016. Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing. Journal of Network and Computer Applications 59, 46--54.

Digital Library

[26]

K. Ha, P. Pillai, W. Richter, Y. Abe, and M. Satyanarayanan. 2013. Just-in-time provisioning for cyber foraging. In Proceeding of the 11th Annual International Conference on Mobile Systems, Applications, and Services. 153--166.

Digital Library

[27]

S. Simanta, K. Ha, G. Lewis, E. Morris, and M. Satyanarayanan. 2012. A reference architecture for mobile code offload in hostile environments. In Proceedings of the International Conference on Mobile Computing, Applications, and Services. 274--293.

[28]

Y. Wu and L. Ying. 2015. A cloudlet-based multi-lateral resource exchange framework for mobile users. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’15). 927--935.

[29]

Y. Zhang, D. Niyato, and P. Wang. 2015. Offloading in mobile cloudlet systems with intermittent connectivity. IEEE Transactions on Mobile Computing 14, 12, 2516--2529.

Digital Library

[30]

A. Bahtovski and M. Gusev. 2014. Cloudlet challenges. Procedia Engineering 69, 704--711.

[31]

Y. Gao, W. Hu, K. Ha, B. Amos, P. Pillai, and M. Satyanarayanan. 2015. Are cloudlets necessary? School of Computer Science. Technical Report CMU-CS-15-139. Carnegie Mellon University, Pittsburgh, PA, USA.

[32]

F. Xia, L. T. Yang, L. Wang, and A. Vinel. 2012. Internet of Things. International Journal of Communication Systems 25, 9, 1101.

Digital Library

[33]

H. Kopetz. 2011. Real-time Systems: Design Principles for Distributed Embedded Applications. New York: Springer Science 8 Business Media.

Digital Library

[34]

L. Atzori, A. Iera, and G. Morabito. 2010. The Internet of Things: A survey. Computer Networks 54, 15, 2787--2805.

Digital Library

[35]

J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami. 2013. Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems 29, 7, 1645--1660.

Digital Library

[36]

T. Nam and T. A. Pardo. 2011. Conceptualizing smart city with dimensions of technology, people, and institutions. In Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times. 282--291.

Digital Library

[37]

A. Cocchia. 2014. Smart and digital city: A systematic literature review. Smart City, 13--43: Springer, 2014.

[38]

K. Su, J. Li, and H. Fu. 2011. Smart city and the applications. In Proceedings of the International Conference on Electronics, Communications and Control (ICECC’11). 1028--1031.

[39]

N. Alhakbani, M. M. Hassan, M. A. Hossain, and M. Alnuem. 2014. A framework of adaptive interaction support in cloud-based Internet of Things (IoT) environment. In Proceedings of the International Conference on Internet and Distributed Computing Systems. 136--146.

[40]

R. Aitken, V. Chandra, J. Myers, B. Sandhu, L. Shifren, and G. Yeric. 2014. Device and technology implications of the Internet of Things. In Symposium on VLSI Technology (VLSI-Technology): Digest of Technical Papers. 1--4.

[41]

M. M. Gomes, R. d. R. Righi, and C. A. da Costa. 2014. Future directions for providing better IoT infrastructure. In Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication. 51--54.

Digital Library

[42]

I. Stojmenovic and S. Wen. 2014. The fog computing paradigm: Scenarios and security issues. In Proceedings of the Federated Conference on Computer Science and Information Systems (FedCSIS’14). 1--8.

[43]

K. Lee, D. Murray, D. Hughes, and W. Joosen. 2010. Extending sensor networks into the cloud using Amazon web services. In Proceedings of the IEEE International Conference on Networked Embedded Systems for Enterprise Applications (NESEA’10). 1--7.

[44]

S. Aguzzi, D. Bradshaw, M. Canning, M. Cansfield, P. Carter, G. Cattaneo, S. Gusmeroli, G. Micheletti, D. Rotondi, and R. Stevens. 2013. Definition of a research and innovation policy leveraging cloud computing and IoT combination. Final Report, European Commission, SMART 37, 2013.

[45]

Y. N. Krishnan, C. N. Bhagwat, and A. P. Utpat. 2015. Fog computing—Network based cloud computing. In Proceedings of the 2nd International Conference on Electronics and Communication Systems (ICECS’15). 250--251.

[46]

E. Ahmed and M. H. Rehmani. 2017. Mobile Edge Computing: Opportunities, Solutions, and Challenges. Elsevier, 59--63.

[47]

D. Sabella, A. Vaillant, P. Kuure, U. Rauschenbach, and F. Giust, 2016. Mobile-edge computing architecture: The role of MEC in the Internet of Things. IEEE Consumer Electronics Magazine 5, 4, 84--91.

[48]

I. Stojmenovic. 2014. Fog computing: A cloud to the ground support for smart things and machine-to-machine networks. In Proceedings of the Australasian Conference on Telecommunication Networks and Applications (ATNAC’14). 117--122.

[49]

F. Bonomi, R. Milito, J. Zhu, and S. Addepalli. 2012. Fog computing and its role in the Internet of Things. In Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing. 13--16.

Digital Library

[50]

T. Taleb, S. Dutta, A. Ksentini, M. Iqbal, and H. Flinck. 2017. Mobile edge computing potential in making cities smarter. IEEE Communications Magazine 55, 3, 38--43.

Digital Library

[51]

A. Manjunatha, A. Ranabahu, A. Sheth, and K. Thirunarayan. 2010. Power of clouds in your pocket: An efficient approach for cloud mobile hybrid application development. In Proceedings of the IEEE Second International Conference on Cloud Computing Technology and Science (CloudCom’10). 496--503.

Digital Library

[52]

Y. Lu, S. Li, and H. Shen. 2011. Virtualized screen: A third element for cloud--mobile convergence. IEEE Multimedia 18, 2, 4--11.

Digital Library

[53]

W. Zheng, P. Xu, X. Huang, and N. Wu. 2010. Design a cloud storage platform for pervasive computing environments. Cluster Computing 13, 2, 141--151.

Digital Library

[54]

P. Stuedi, I. Mohomed, and D. Terry. 2010. Wherestore: Location-based data storage for mobile devices interacting with the cloud. In Proceedings of the 1st ACM Workshop on Mobile Cloud Computing 8 Services: Social Networks and Beyond.

Digital Library

[55]

V. March, Y. Gu, E. Leonardi, G. Goh, M. Kirchberg, and B. S. Lee. 2011. μcloud: Towards a new paradigm of rich mobile applications. Procedia Computer Science 5, 618--624.

[56]

H. Mao, N. Xiao, W. Shi, and Y. Lu. 2012. Wukong: A cloud-oriented file service for mobile Internet devices. Journal of Parallel and Distributed Computing 72, 2, 171--184.

Digital Library

[57]

S.-H. Hung, C.-S. Shih, J.-P. Shieh, C.-P. Lee, and Y.-H. Huang. 2012. Executing mobile applications on the cloud: Framework and issues. Computers 8 Mathematics with Applications 63, 2, 573--587.

Digital Library

[58]

B.-G. Chun, S. Ihm, P. Maniatis, M. Naik, and A. Patti. 2011. Clonecloud: elastic execution between mobile device and cloud. In Proceedings of the Sixth Conference on Computer Systems. 301--314.

Digital Library

[59]

X. Zhang, A. Kunjithapatham, S. Jeong, and S. Gibbs. 2011. Towards an elastic application model for augmenting the computing capabilities of mobile devices with cloud computing. Mobile Networks and Applications 16, 3, 270--284.

Digital Library

[60]

M. Satyanarayanan, P. Bahl, R. Caceres, and N. Davies. 2009. The case for VM-based cloudlets in mobile computing. IEEE Pervasive Computing 8, 4, 2009.

Digital Library

[61]

G. Huerta-Canepa and D. Lee. 2010. A virtual cloud computing provider for mobile devices. In Proceedings of the 1st ACM Workshop on Mobile Cloud Computing 8 Services: Social Networks and Beyond.

Digital Library

[62]

S. Abolfazli, Z. Sanaei, M. Shiraz, and A. Gani. 2012. MOMCC: Market-oriented architecture for mobile cloud computing based on service oriented architecture. In Proceedings of the 1st IEEE International Conference on Communications in China Workshops (ICCC’12). 8--13.

[63]

M. P. Papazoglou. 2003. Service-oriented computing: Concepts, characteristics and directions. In Proceedings of the Fourth International Conference on Web Information Systems Engineering (WISE’03). IEEE, 3--12.

Digital Library

[64]

E. E. Marinelli. 2009. Hyrax: Cloud Computing on Mobile Devices Using MapReduce No. CMU-CS-09-164. Carnegie-mellon Univ. Pittsburgh PA school of computer science.

[65]

D. Van Le and C.-K. Tham. 2017. An optimization-based approach to offloading in ad-hoc mobile clouds. In IEEE Global Communications Conference (GLOBECOM’17). 1--6.

Digital Library

[66]

S. Chilukuri, S. Bollapragada, S. Kommineni, and K. Chakravarthy. 2017. RainCloud-cloudlet selection for effective cyber foraging. In Wireless Communications and Networking Conference (WCNC’17). IEEE, 1--6.

[67]

T. Soyata, R. Muraleedharan, C. Funai, M. Kwon, and W. Heinzelman. 2012. Cloud-vision: Real-time face recognition using a mobile-cloudlet-cloud acceleration architecture. In IEEE Symposium on Computers and Communications (ISCC’12). 59--66.

Digital Library

[68]

Z. Sanaei, S. Abolfazli, A. Gani, and M. Shiraz. 2012. SAMI: Service-based arbitrated multi-tier infrastructure for mobile cloud computing. In Proceedings of the 1st IEEE International Conference on Communications in China Workshops (ICCC’12). 14--19.

[69]

N. Fernando, S. W. Loke, and W. Rahayu. 2013. Mobile cloud computing: A survey. Future Generation Computer Systems 29, 1, 84--106.

Digital Library

[70]

H. Raei and N. Yazdani. 2017. Analytical performance models for resource allocation schemes of cloudlet in mobile cloud computing. The Journal of Supercomputing 73, 3 (2017), 1274--1305.

Digital Library

[71]

H. T. Dinh, C. Lee, D. Niyato, and P. Wang. 2013. A survey of mobile cloud computing: architecture, applications, and approaches. Wireless Communications and Mobile Computing 13, 18, 1587--1611.

[72]

Y. Jararweh, L. Tawalbeh, F. Ababneh, and F. Dosari. 2013. Resource efficient mobile computing using cloudlet infrastructure. In Proceedings of the IEEE Ninth International Conference on Mobile Ad-hoc and Sensor Networks (MSN’13). 373--377.

Digital Library

[73]

A. Beloglazov, J. Abawajy, and R. Buyya. 2012. Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Generation Computer Systems 28, 5, 755--768.

Digital Library

[74]

Z. Jiang and S. Mao. 2015. Energy delay tradeoff in cloud offloading for multi-core mobile devices. IEEE Access 3, 2306--2316.

[75]

K. Gai, M. Qiu, and H. Zhao. 2018. Energy-aware task assignment for mobile cyber-enabled applications in heterogeneous cloud computing. Journal of Parallel and Distributed Computing 111, 126--135.

Digital Library

[76]

A. Hooper. 2008. Green computing, Communications of the ACM 51, 10, 11--13.

Digital Library

[77]

N. J. Kansal and I. Chana. 2012. Cloud load balancing techniques: A step towards green computing. IJCSI International Journal of Computer Science Issues 9, 1, 238--246.

[78]

X. Sun and N. Ansari. 2016. Green cloudlet network: A distributed green mobile cloud network. Arxiv Preprint Arxiv:1605.07512.

Digital Library

[79]

X. Lyu, H. Tian, L. Jiang, A. Vinel, S. Maharjan, S. Gjessing, and Y. Zhang. 2018. Selective offloading in mobile edge computing for the green Internet of Things. IEEE Network 32, 1, 54--60.

[80]

J. Zhang, W. Xia, Y. Zhang, Q. Zou, B. Huang, F. Yan, and L. Shen. 2017. Joint offloading and resource allocation optimization for mobile edge computing. In IEEE Global Communications Conference (GLOBECOM’17). 1--6.

[81]

A. Hameed, A. Khoshkbarforoushha, R. Ranjan, P. P. Jayaraman, J. Kolodziej, P. Balaji, S. Zeadally, Q. M. Malluhi, N. Tziritas, and A. Vishnu. 2016. A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems. Computing, 98, 7, 751--774.

Digital Library

[82]

S. Bohez, T. Verbelen, P. Simoens, and B. Dhoedt. 2015. Discrete-event simulation for efficient and stable resource allocation in collaborative mobile cloudlets. Simulation Modelling Practice and Theory 50, 109--129.

[83]

M. Jia, J. Cao, and W. Liang. 2017. Optimal cloudlet placement and user to cloudlet allocation in wireless metropolitan area networks. IEEE Transactions on Cloud Computing 5, 4 (2017), 725--737.

[84]

K. Ha, Y. Abe, Z. Chen, W. Hu, B. Amos, P. Pillai, and M. Satyanarayanan. 2015. Adaptive vm Handoff Across Cloudlets. Technical Report CMU-CS-15--113, CMU School of Computer Science.

[85]

G. Lewis, S. Echeverría, S. Simanta, B. Bradshaw, and J. Root. 2014. Tactical cloudlets: Moving cloud computing to the edge. In IEEE Conference on Military Communications (MILCOM’14). 1440--1446.

Digital Library

[86]

J. Hu, J. Gu, G. Sun, and T. Zhao. 2010. A scheduling strategy on load balancing of virtual machine resources in cloud computing environment. In Proceedings of the Third International Symposium on Parallel Architectures, Algorithms and Programming (PAAP’10). 89--96.

Digital Library

[87]

S. Goyal and J. Carter. 2004. A lightweight secure cyber foraging infrastructure for resource-constrained devices. In Proceedings of the Sixth IEEE Workshop on Mobile Computing Systems and Applications (WMCSA’04). 186--195.

Digital Library

[88]

B.-G. Chun and P. Maniatis. 2009. Augmented smartphone applications through clone cloud execution. In HotOS. 8--11.

Digital Library

[89]

B. Zhao, Z. Xu, C. Chi, S. Zhu, and G. Cao. 2010. Mirroring smartphones for good: A feasibility study. In International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services. 26--38.

[90]

A. Dou, V. Kalogeraki, D. Gunopulos, T. Mielikainen, and V. H. Tuulos. 2010. Misco: A mapreduce framework for mobile systems. In Proceedings of the 3rd International Conference on Pervasive Technologies Related to Assistive Environments.

Digital Library

[91]

R. Iyer, S. Srinivasan, O. Tickoo, Z. Fang, R. Illikkal, S. Zhang, V. Chadha, P. Stillwell, and S. E. Lee. 2011. Cogniserve: Heterogeneous server architecture for large-scale recognition. IEEE Micro 31, 3, 20--31.

Digital Library

[92]

Q. Liu, X. Jian, J. Hu, H. Zhao, and S. Zhang. 2009. An optimized solution for mobile environment using mobile cloud computing. In Proceedings of the 5th International Conference on Wireless Communications, Networking and Mobile Computing. 1--5.

Digital Library

[93]

C. Lai, and R.-S. Ko. 2010. Dishes: A distributed shell system designed for ubiquitous computing environment. International Journal of Computer Networks 8 Communications 2, 1, 66--83.

[94]

J. Liu, E. Ahmed, M. Shiraz, A. Gani, R. Buyya, and A. Qureshi. 2015. Application partitioning algorithms in mobile cloud computing: Taxonomy, review and future directions. Journal of Network and Computer Applications 48, 99--117.

Digital Library

[95]

B.-G. Chun and P. Maniatis. 2010. Dynamically partitioning applications between weak devices and clouds. In Proceedings of the 1st ACM Workshop on Mobile Cloud Computing 8 Services: Social Networks and Beyond.

Digital Library

[96]

M. Shiraz, A. Gani, R. H. Khokhar, and R. Buyya. 2013. A review on distributed application processing frameworks in smart mobile devices for mobile cloud computing. IEEE Communications Surveys 8 Tutorials 15, 3, 1294--1313.

[97]

A. Messer, I. Greenberg, P. Bernadat, D. Milojicic, D. Chen, T. J. Giuli, and X. Gu. 2002. Towards a distributed platform for resource-constrained devices. In Proceedings of the 22nd International Conference on Distributed Computing Systems. 43--51.

Digital Library

[98]

E. Cuervo, A. Balasubramanian, D.-k. Cho, A. Wolman, S. Saroiu, R. Chandra, and P. Bahl. 2010. MAUI: making smartphones last longer with code offload. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services. 49--62.

Digital Library

[99]

H. Wu and K. Wolter. 2015. Software aging in mobile devices: Partial computation offloading as a solution. In Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW’15). 125--131.

Digital Library

[100]

X. Gu, K. Nahrstedt, A. Messer, I. Greenberg, and D. Milojicic. 2004. Adaptive offloading for pervasive computing. IEEE Pervasive Computing 3, 3, 66--73.

Digital Library

[101]

K. Kumar, J. Liu, Y.-H. Lu, and B. Bhargava. 2013. A survey of computation offloading for mobile systems. Mobile Networks and Applications 18, 1, 129--140.

Digital Library

[102]

H. Flores, R. Sharma, D. Ferreira, V. Kostakos, J. Manner, S. Tarkoma, P. Hui, and Y. Li. 2017. Socialaware hybrid mobile offloading. Pervasive and Mobile Computing 36, 25--43.

Digital Library

[103]

B. Zhou, A. V. Dastjerdi, R. N. Calheiros, S. N. Srirama, and R. Buyya. 2015. A context sensitive offloading scheme for mobile cloud computing service. In IEEE 8th International Conference on Cloud Computing (CLOUD’15). 869--876.

Digital Library

[104]

Y. Zhang, D. Niyato, P. Wang, and C.-K. Tham. 2014. Dynamic offloading algorithm in intermittently connected mobile cloudlet systems. In IEEE International Conference on Communications (ICC’14). 4190--4195.

[105]

L. Tang, X. Chen, and S. He. 2016. When social network meets mobile cloud: A social group utility approach for optimizing computation offloading in cloudlet. IEEE Access 4, 5868--5879.

[106]

R. Niu, W. Song, and Y. Liu. 2013. An energy-efficient multisite offloading algorithm for mobile devices. International Journal of Distributed Sensor Networks 9, 2013.

[107]

D. Huang, P. Wang, and D. Niyato. 2012. A dynamic offloading algorithm for mobile computing. IEEE Transactions on Wireless Communications 11, 1991--1995.

[108]

Z. Sanaei, S. Abolfazli, A. Gani, and R. Buyya. 2014. Heterogeneity in mobile cloud computing: Taxonomy and open challenges. IEEE Communications Surveys 8 Tutorials 16, 1, 369--392.

[109]

T. Dillon, C. Wu, and E. Chang. 2010. Cloud computing: Issues and challenges. In IEEE International Conference on Advanced Information Networking and Applications (AINA’10). 27--33.

Digital Library

[110]

N. Leavitt. 2009. Is cloud computing really ready for prime time? Growth 27, 15--20.

Digital Library

[111]

M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, and I. Stoica. 2010. A view of cloud computing. Communications of the ACM 53, 4, 50--58.

Digital Library

[112]

K. So. 2011. Cloud computing security issues and challenges. International Journal of Computer Networks 3, 5, 247--255.

[113]

K. Gai and M. Qiu. 2018. Blend arithmetic operations on tensor-based fully homomorphic encryption over real numbers. IEEE Transactions on Industrial Informatics 14, 3590--3598.

[114]

S. Subashini and V. Kavitha. 2011. A survey on security issues in service delivery models of cloud computing. Journal of Network and Computer Applications 34, 1, 1--11.

Digital Library

[115]

K. Gai, M. Qiu, and X. Sun. 2011. A survey on fintech. Journal of Network and Computer Applications.

[116]

D. Novakovic, N. Vasic, S. Novakovic, D. Kostic, and R. Bianchini. 2013. Deepdive: Transparently identifying and managing performance interference in virtualized environments. In Proceedings of the 2013 USENIX Conference on Annual Technical Conference.

Digital Library

[117]

A. Zanella, N. Bui, A. Castellani, L. Vangelista, and M. Zorzi. 2014. Internet of Things for smart cities. IEEE Internet of Things Journal 1, 1, 22--32.

[118]

A. Botta, W. De Donato, V. Persico, and A. Pescapé. 2016. Integration of cloud computing and Internet of Things: A survey. Future Generation Computer Systems 56, 684--700.

Digital Library

[119]

M. Jo, T. Maksymyuk, B. Strykhalyuk, and C.-H. Cho. 2015. Device-to-device-based heterogeneous radio access network architecture for mobile cloud computing. IEEE Wireless Communications 22, 3, 50--58.

Digital Library

[120]

F. Vargas Vargas. 2016. Cloudlet for the Internet-of-Things. TRITA-ICT-EX, 119.

[121]

Z. Zhang and X. Zhang. 2009. Realization of open cloud computing federation based on mobile agent. In IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS’09). 642--646.

[122]

F. Teka, C.-H. Lung, and S. Ajila. 2015. Seamless live virtual machine migration with cloudlets and multipath TCP. In Proceedings of the IEEE 39th Annual Conference on Computer Software and Applications (COMPSAC’15). 607--616.

Digital Library

[123]

W. Shi, J. Cao, Q. Zhang, Y. Li, and L. Xu. 2016. Edge computing: Vision and challenges. IEEE Internet of Things Journal 3, 5, 637--646.

[124]

J. Lanza, L. Sánchez, V. Gutiérrez, J. A. Galache, J. R. Santana, P. Sotres, and L. Muñoz. 2016. Smart city services over a future Internet platform based on Internet of Things and cloud: The smart parking case. Energies 9.

[125]

D. Fesehaye, Y. Gao, K. Nahrstedt, and G. Wang. 2012. Impact of cloudlets on interactive mobile cloud applications. In IEEE 16th International Conference on Enterprise Distributed Object Computing (EDOC’12). 123--132.

Digital Library

[126]

K. Wang, M. Shen, J. Cho, A. Banerjee, J. Van der Merwe, and K. Webb. 2015. Mobiscud: A fast moving personal cloud in the mobile network. In Proceedings of the 5th Workshop on All Things Cellular: Operations, Applications and Challenges. 19--24.

Digital Library

[127]

R. Agarwal and A. Nayak. 2015. DRAP: A decentralized public resourced cloudlet for ad-hoc networks. In Proceedings of the 4th IEEE International Conference on Cloud Networking (CloudNet’15). 309--314.

[128]

W. Fang, X. Yao, X. Zhao, J. Yin, and N. Xiong. 2016. A stochastic control approach to maximize profit on service provisioning for mobile cloudlet platforms. IEEE Transactions on Systems, Man, and Cybernetics: Systems 48, 4 (2016), 522--534.

[129]

M. J. Neely. 2010. Stochastic network optimization with application to communication and queueing systems. Synthesis Lectures on Communication Networks 3, 1, 1--211.

Digital Library

[130]

X. Guo, L. Liu, Z. Chang, and T. Ristaniemi. 2018. Data offloading and task allocation for cloudlet-assisted ad hoc mobile clouds. Wireless Networks 24, 1 (2018), 1--10.

Digital Library

[131]

J. Rawadi, H. Artail, and H. Safa. 2014. Providing local cloud services to mobile devices with inter-cloudlet communication. In Proceedings of the 17th IEEE Conference on Mediterranean Electrotechnical (MELECON’14). 134--138.

[132]

Y. Chen, Y. Chen, Q. Cao, and X. Yang, 2016. PacketCloud: A cloudlet-based open platform for in-network services. IEEE Transactions on Parallel and Distributed Systems 27, 4, 1146--1159.

Digital Library

[133]

M. Chen, Y. Hao, Y. Li, C.-F. Lai, and D. Wu. 2015. On the computation offloading at ad hoc cloudlet: architecture and service modes. IEEE Communications Magazine 53, 6, 18--24.

Digital Library

[134]

R. W. Klein and R. C. Dubes. 1989. Experiments in projection and clustering by simulated annealing. Pattern Recognition 22, 2, 213--220.

[135]

G. Arfken. 1985. The method of steepest descents. Mathematical Methods for Physicists 3, 428--436.

[136]

S. Bohez, J. De Turck, T. Verbelen, P. Simoens, and B. Dhoedt. 2013. Mobile, collaborative augmented reality using cloudlets. In International Conference on Mobile Wireless MiddleWARE, Operating Systems and Applications (Mobilware’13). 45--54.

Digital Library

[137]

Y. Jararweh, F. Ababneh, A. Khreishah, and F. Dosari. 2014. Scalable cloudlet-based mobile computing model. Procedia Computer Science 34, 434--441.

[138]

K. A. Khan, Q. Wang, C. Grecos, C. Luo, and X. Wang. 2013. MeshCloud: Integrated cloudlet and wireless mesh network for real-time applications. In Proceedings of the IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS’13). 317--320.

Cited By

Jaiswal AThakare VChaurasia SPonnusamy SSharma B(2024)A framework for Optimizing Resources and Performance Management in Cloudlet Computing Environment2024 Control Instrumentation System Conference (CISCON)10.1109/CISCON62171.2024.10696672(1-5)Online publication date: 2-Aug-2024
https://doi.org/10.1109/CISCON62171.2024.10696672
Cao LHuo TLi SZhang XChen YLin GWu FLing YZhou YXie Q(2024)Cost optimization in edge computing: a surveyArtificial Intelligence Review10.1007/s10462-024-10947-457:11Online publication date: 1-Oct-2024
https://doi.org/10.1007/s10462-024-10947-4
Shahid VNayyer MAhmed U(2023)Trust-aware Cloudlet Federation Model for Secure Service Selection2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)10.1109/ICEPECC57281.2023.10209493(1-5)Online publication date: 8-Mar-2023
https://doi.org/10.1109/ICEPECC57281.2023.10209493
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Index Terms

A Survey of Cloudlet-Based Mobile Augmentation Approaches for Resource Optimization
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
      1. Cloud computing
2. General and reference
  1. Document types
    1. Surveys and overviews

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 51, Issue 5

September 2019

791 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3271482

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering

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Copyright © 2018 ACM.

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Publication History

Published: 19 November 2018

Accepted: 01 July 2018

Revised: 01 May 2018

Received: 01 January 2018

Published in CSUR Volume 51, Issue 5

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Cited By

Jaiswal AThakare VChaurasia SPonnusamy SSharma B(2024)A framework for Optimizing Resources and Performance Management in Cloudlet Computing Environment2024 Control Instrumentation System Conference (CISCON)10.1109/CISCON62171.2024.10696672(1-5)Online publication date: 2-Aug-2024
https://doi.org/10.1109/CISCON62171.2024.10696672
Cao LHuo TLi SZhang XChen YLin GWu FLing YZhou YXie Q(2024)Cost optimization in edge computing: a surveyArtificial Intelligence Review10.1007/s10462-024-10947-457:11Online publication date: 1-Oct-2024
https://doi.org/10.1007/s10462-024-10947-4
Shahid VNayyer MAhmed U(2023)Trust-aware Cloudlet Federation Model for Secure Service Selection2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)10.1109/ICEPECC57281.2023.10209493(1-5)Online publication date: 8-Mar-2023
https://doi.org/10.1109/ICEPECC57281.2023.10209493
Kumar BSingh MVerma AVerma P(2023)Optimal Cloudlet Selection in Edge Computing for Resource AllocationSN Computer Science10.1007/s42979-023-02187-04:6Online publication date: 26-Sep-2023
https://dl.acm.org/doi/10.1007/s42979-023-02187-0
Pramanik PPal SChoudhury P(2023)Mobile crowd computing: potential, architecture, requirements, challenges, and applicationsThe Journal of Supercomputing10.1007/s11227-023-05545-080:2(2223-2318)Online publication date: 29-Jul-2023
https://dl.acm.org/doi/10.1007/s11227-023-05545-0
Alakbarov R(2022)An Optimization Model for Task Scheduling in Mobile Cloud ComputingInternational Journal of Cloud Applications and Computing10.4018/IJCAC.29710212:1(1-17)Online publication date: 29-Apr-2022
https://doi.org/10.4018/IJCAC.297102
Ahlawat PSangwan S(2022)Task Scheduling on Cloudlet in Mobile Cloud Computing with Load BalancingInternational Journal of Electrical and Electronics Research10.37391/ijeer.10044010:4(994-998)Online publication date: 30-Dec-2022
https://doi.org/10.37391/ijeer.100440
Boursalie OSamavi RDoyle T(2022)Evaluation methodology for deep learning imputation modelsExperimental Biology and Medicine10.1177/15353702221121602247:22(1972-1987)Online publication date: 21-Sep-2022
https://doi.org/10.1177/15353702221121602
Nayyer MRaza IHussain SJamal MGillani ZHur SAshraf I(2022)LBRO: Load Balancing for Resource Optimization in Edge ComputingIEEE Access10.1109/ACCESS.2022.320574110(97439-97449)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3205741
Dimou AIliopoulos CPolytidou EDhurandher SPapadimitriou GNicopolitidis P(2022)A Comprehensive Review on Edge Computing: Focusing on Mobile UsersAdvances in Computing, Informatics, Networking and Cybersecurity10.1007/978-3-030-87049-2_30(121-152)Online publication date: 3-Mar-2022
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