A bi-objective hybrid genetic algorithm to minimize energy consumption and makespan for precedence-constrained applications using dynamic voltage scaling

2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Volumn , Issue , 2010, Pages

  Mezmaz, Mohand ^a   Lee, Young Choon ^b   Melab, Nouredine ^c   Talbi, El Ghazali ^c   Zomaya, Albert Y ^b  

^a UNIVERSITY OF MONS   (Belgium)

^b UNIVERSITY OF SYDNEY   (Australia)

^c INRIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPARATIVE EVALUATIONS; COMPLETION TIME; DYNAMIC VOLTAGE SCALING; ENGINEERING FIELDS; HETEROGENEOUS COMPUTING SYSTEM; HYBRID GENETIC ALGORITHMS; MAKESPAN; METAHEURISTIC; PARALLEL APPLICATION; TYPICAL APPLICATION;

ARTIFICIAL INTELLIGENCE; ENERGY UTILIZATION; GENETIC ALGORITHMS; SCHEDULING ALGORITHMS;

VOLTAGE STABILIZING CIRCUITS;

EID: 79959382493     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2010.5586540     Document Type: Conference Paper

References (26)

1. S. Darbha and D. P. Agrawal, Optimal scheduling algorithm for distributed-memory machines, IEEE Trans. Parallel Dist. Systems, vol. 9, no. 1, 1998, pp. 87-95.
2. A. Y. Zomaya, C. Ward, and B. S. Macey, Genetic Scheduling for Parallel Processor Systems: Comparative Studies and Performance Issues, IEEE Trans. Parallel Dist. Systems, vol. 10, no. 8, pp. 795-812, 1999.
3. H. Topcuouglu, S. Hariri, and M.Y. Wu, Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing, IEEE Trans. Parallel Dist. Systems, vol. 13, no. 3, pp. 260-274, 2002.
4. Y. C. Lee and A. Y. Zomaya, A Novel State Transition Method for meta-heuristic-Based Scheduling in Heterogeneous Computing Systems, IEEE Trans. Parallel and Dist. Systems, vol. 19, no. 9, pp. 1215-1223, Sep. 2008.
5. K. H. Kim, R. Buyya, and J. Kim, Power Aware Scheduling of Bag-of-Tasks Applications with Deadline Constraints on DVS-enabled Clusters, Proc. the Seventh IEEE Int'l Symp. Cluster Computing and the Grid, May 2007.
6. D. P. Bunde, Power-aware scheduling for makespan and flow, Proc. the eighteenth annual ACM symposium on Parallelism in algorithms and architectures, July 2006.
7. D. Zhu, R. Melhem, and B. R. Childers, Scheduling with dynamic voltage/speed adjustment using slack reclamation in multiprocessor real-time systems, IEEE Trans. Parallel Dist. Systems, vol. 14, no. 7, pp. 686-700, 2003.
8. D. Zhu, D. Mosse, and R.Melhem, Power-aware scheduling for AND/OR graphs in real-time systems, IEEE Trans. Parallel Dist. Systems, vol. 15, no. 9, pp. 849-864, 2004.
9. R. Ge, X. Feng, and K.W. Cameron, Performance-constrained Distributed DVS Scheduling for Scientific Applications on Power-aware Clusters, Proc. the ACM/IEEE Conference on Supercomputing, pp.34-44, November 2005.
10. B. Rountree, D. K. Lowenthal, S. Funk, V. W. Freeh, B. R. de Supinski, M. Schulz, Bounding energy consumption in large-scale MPI programs, Proc. the ACM/IEEE conference on Supercomputing, November 2007.
11. J. G. Koomey, Estimating total power consumption by servers in the U.S. and the world.
12. G. Koch, Discovering multi-core: extending the benefits of Moore's law, Technology@Intel Magazine, July 2005.
13. V. Venkatachalam and M. Franz, Power reduction techniques for microprocessor systems, ACM Computing Survey, vol. 37, no. 3, September 2005, pp. 195-237.
14. Intel, Intel Pentium M Processor datasheet, 2004.
15. R. Min, T. Furrer, and A. Chandrakasan, Dynamic Voltage Scaling Techniques for Distributed Microsensor Networks, Proc. IEEE Workshop on VLSI, pp. 43-46, April 2000.
16. M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, W.H. Freeman and Co., pp. 238-239, 1979.
17. Y. K. Kwok and I. Ahmad, Benchmarking the Task Graph Scheduling Algorithms, Proc. First Merged Int'l Parallel Symposium/Symposium on Parallel and Distributed Processing (IPPS/SPDP '98), pp. 531-537, 1998.
18. D. Bozdag, U. Catalyurek and F. Ozguner, A task duplication based bottom-up scheduling algorithm for heterogeneous environments, Proc. Int'l Parallel and Distributed Processing Symp., April 2005.
19. J. J. Chen and T. W. Kuo, Multiprocessor Energy-Efficient Scheduling for Real-Time Tasks with Different Power Characteristics, Proc. Int'l Conf. Parallel Processing, pp. 13-20, 2005.
20. X. Zhong and C.-Z. Xu, Energy-aware modeling and scheduling for dynamic voltage scaling with statistical real-time guarantee, IEEE Trans. Computers, vol. 56, no. 3, pp. 358-372, 2007.
21. T.H. Cormen, C.E. Leiserson, and R.L. Rivest, Introduction to Algorithms, MIT Press, 1990.
22. S. C. Kim, S. Lee and J. Hahm, Push-Pull: Deterministic Search-Based DAG Scheduling for Heterogeneous Cluster Systems, IEEE Trans. Parallel Dist. Systems, vol. 18, no. 11, pp. 1489-1502, 2007.
23. Y. C. Lee and A. Y. Zomaya, A Productive Duplication-Based Scheduling Algorithm for Heterogeneous Computing Systems, Proc. Int'l Conf. High Performance Computing and Communications (HPCC), pp. 203-212, 2005.
24. Y. Choon Lee and A. Y. Zomaya, Minimizing Energy Consumption for Precedence-Constrained Applications Using Dynamic Voltage Scaling, CCGRID'09: Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 92-99, 2009.
25. S. Cahon, N. Melab and E-G. Talbi, ParadisEO: A Framework for the Reusable Design of Parallel and Distributed metaheuristics, Journal of Heuristics, vol. 10(3), pp.357-380, May 2004.
26. L. Wang , G. von Laszewski and J. Dayal, Towards Energy Aware Scheduling for Precedence Constrained Parallel Tasks in a Cluster with DVFS, CCGRID'10: The 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, May 17-20, 2010, Melbourne, Victoria, Australia.