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Latency modeling and minimization for large-scale scientific workflows in distributed network environments

Published: 03 April 2011 Publication History

Abstract

Large-scale e-science applications feature complex workflows consisting of many computing modules. Mapping such workflows in distributed network environments and minimizing their latency are crucial to those applications that require fast system response and prompt user interaction. We model the time cost of each workflow component and design an efficient algorithm to compute the exact end-to-end delay of the entire workflow by explicitly accounting for the resource sharing dynamics. We further propose a workflow mapping approach to minimize the workflow latency using a recursive optimization procedure. The validity of the cost models and the accuracy of the latency computing algorithm are verified in comparison with an approximate solution, a dynamic system simulation program, and a workflow engine deployed in a real network. The performance superiority of the proposed mapping approach is illustrated by extensive simulation-based comparisons with existing algorithms.

References

[1]
B. Agarwalla, N. Ahmed, D. Hilley, and U. Ramachandran. Streamline: a scheduling heuristic for streaming application on the grid. In Proc. of the 13th Multimedia Comp. and Net. Conf., San Jose, CA, 2006.
[2]
A. F. Bashir, V. Susarla, and K. Vairavan. A statistical study of the performance of a task scheduling algorithm. IEEE Trans. on Computers, 32(12):774--777, Dec. 1975.
[3]
C. Boeres, J. V. Filho, and V. E. F. Rebello. A cluster-based strategy for scheduling task on heterogeneous processors. In Proc. of 16th Symp. on Computer Architecture and High Performance Computing, pages 214--221, 2004.
[4]
D. Bozdag, U. Catalyurek, and F. Ozguner. A task duplication based bottom-up scheduling algorithm for heterogeneous environments. In Proc. of the 20th Int. Parallel and Distributed Processing Symposium, Apr. 2006.
[5]
T. D. Braun, H. J. Siegel, N. Beck, L. L. Boloni, M. Maheswaran, A. I. Reuther, J. P. Robertson, M. D. Theys, B. Yao, D. Hensgen, and R. F. Freund. A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems. JPDC, 61(6):810--837, June 2001.
[6]
V. Chaudhary and J. K. Aggarwal. A generalized scheme for mapping parallel algorithms. IEEE Trans. on Parallel and Distributed Systems, 4(3):328--346, May 1993.
[7]
L. Chen and G. Agrawal. Resource allocation in a middleware for streaming data. In Proc. of the 2nd Workshop on Middleware for Grid Comp., Toronto, Canada, Oct. 2004.
[8]
L. P. Cordella, P. Foggia, C. Sansone, and M. Vento. An improved algorithm for matching large graphs. In Proc. of the 3rd IAPR-TC-15 Int. Workshop on Graph-based Representations, Italy, 2001.
[9]
A. Gerasoulis and T. Yang. A comparison of clustering heuristics for scheduling DAGs on multiprocessors. JPDC, 16(4):276--291, Dec. 1992.
[10]
J. Hopcroft and J. Wong. Linear time algorithm for isomorphism of planar graphs. In Proc. of the 6th Annual ACM Symp., Theory of Computing, pages 172--184, 1974.
[11]
Y. Kwok and I. Ahmad. Dynamic critical-path scheduling: An effective technique for allocating task graph to multiprocessors. IEEE Trans. on Parallel and Distributed Systems, 7(5):506--521, May 1996.
[12]
Y. Kwok and I. Ahmad. Static scheduling algorithms for allocating directed task graphs to multiprocessors. ACM Computing Surveys, 31(4):406--471, Dec. 1999.
[13]
E. M. Luks. Isomorphism of graphs of bounded valence can be tested in polynomial time. J. of Computer System Science, pages 42--65, 1982.
[14]
T. Ma and R. Buyya. Critical-path and priority based algorithms for scheduling workflows with parameter sweep tasks on global grids. In Proc. of the 17th Int. Symp. on Computer Architecture on HPC, pages 251--258, 2005.
[15]
C. McCreary, A. A. Khan, J. J. Thompson, and M. E. McArdle. A comparison of heuristics for scheduling DAGs on multiprocessors. In Proc. of the 8th Int. Symp. on Parallel Processing, pages 446--451. IEEE Computer Society, 1994.
[16]
B. T. Messmer. Efficient Graph Matching Algorithms for Pre-processed Model Graphs. PhD thesis, Institute of Computer Science and Applied Mathematics, University of Bern, 1996.
[17]
M. Rahman, S. Venugopal, and R. Buyya. A dynamic critical path algorithm for scheduling scientific workflow applications on global grids. In Proc. of the 3rd IEEE Int. Conf. on e-Sci. and Grid Comp., pages 35--42, 2007.
[18]
A. Sekhar, B. S. Manoj, and C. S. R. Murthy. A state-space search approach for optimizing reliability and cost of execution in distributed sensor networks. In Proc. of Int. Workshop on Dist. Comp., pages 63--74, 2005.
[19]
B. Shirazi, M. Wang, and G. Pathak. Analysis and evaluation of heuristic methods for static scheduling. J. of Parallel and Distributed Computing, (10):222--232, 1990.
[20]
P. Shroff, D. W. Watson, N. S. Flann, and R. F. Freund. Genetic simulated annealing for scheduling data-dependent tasks in heterogeneous environments. In Proc. of Heterogeneous Computing Workshop, pages 98--104, Apr. 1996.
[21]
G. C. Sih and E. A. Lee. A compile-time scheduling heuristic for interconnection-constrained heterogeneous processor architectures. IEEE Trans. on Para. and Dist. Systems, 4(2):175--187, 1993.
[22]
H. Topcuoglu, S. Hariri, and M. Y. Wu. Performance effective and low-complexity task scheduling for heterogeneous computing. IEEE Trans. on Parallel and Distributed Systems, 13(3), 2002.
[23]
L. Wang, H. J. Siege, V. P. Roychowdhury, and A. A. Maciejewski. Task matching and scheduling in heterogeneous computing environments using a genetic-algorithm-based approach. J. of Parallel and Distributed Computing, 47:8--22, 1997.
[24]
M. Wieczorek, R. Prodan, and T. Fahringer. Scheduling of scientific workflows in the ASKALON grid environment. ACM SIGMOD, Record J., 34(3):56--62, Sep. 2005.
[25]
Q. Wu and Y. Gu. Supporting distributed application workflows in heterogeneous computing environments. In Proc. of the 14th IEEE Int. Conf. on Parallel and Distributed Systems, pages 3--10, Melbourne, Australia, Dec. 2008.
[26]
Q. Wu, Y. Gu, and Z. Wang. Simulation-based analysis of performance dynamics of distributed applications in heterogeneous network environments. In SpringSim'09: Proc. of the 2009 Spring Simulation Multiconference, pages 1--8, San Diego, CA, March 22--27 2009.
[27]
Q. Wu, M. Zhu, X. Lu, P. Brown, Y. Lin, Y. Gu, F. Cao, and M. A. Reuter. Automation and management of scientific workflows in distributed network environments. In Proc. of the 6th Int. Workshop on Sys. Man. Tech., Proc., and Serv., Atlanta, GA, April 19 2010.

Cited By

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  • (2018)Decentralised hybrid workflow scheduling algorithm for minimum end-to-end delay in heterogeneous computing environmentInternational Journal of High Performance Computing and Networking10.1504/IJHPCN.2015.0727838:4(324-336)Online publication date: 19-Dec-2018
  • (2018)A Distributed Workflow Management System with Case Study of Real-life Scientific Applications on GridsJournal of Grid Computing10.1007/s10723-012-9222-710:3(367-393)Online publication date: 15-Dec-2018

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Published In

cover image ACM Other conferences
ANSS '11: Proceedings of the 44th Annual Simulation Symposium
April 2011
238 pages
ISBN:1930638566

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  • SCS: Society for Modeling and Simulation International

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Society for Computer Simulation International

San Diego, CA, United States

Publication History

Published: 03 April 2011

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Author Tags

  1. distributed computing
  2. latency
  3. modeling
  4. workflow

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  • Research-article

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SpringSim '11
Sponsor:
  • SCS
SpringSim '11: 2011 Spring Simulation Multi-conference
April 3 - 7, 2011
Massachusetts, Boston

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Cited By

View all
  • (2018)Decentralised hybrid workflow scheduling algorithm for minimum end-to-end delay in heterogeneous computing environmentInternational Journal of High Performance Computing and Networking10.1504/IJHPCN.2015.0727838:4(324-336)Online publication date: 19-Dec-2018
  • (2018)A Distributed Workflow Management System with Case Study of Real-life Scientific Applications on GridsJournal of Grid Computing10.1007/s10723-012-9222-710:3(367-393)Online publication date: 15-Dec-2018

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