Algorithms: Memetic Algorithms for Energy-Aware Computation and Communications Optimization in Computing Clusters

Handbook of Energy-Aware and Green Computing-Two Volume Set

Volumn 1, Issue , 2016, Pages 443-472

  Pecero, Johnatan E ^a   Dorronsoro, Bernabé ^a   Guzek, Mateusz ^a   Bouvry, Pascal ^a  

^a UNIVERSITY OF LUXEMBOURG   (Luxembourg)

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EID: 84886891997     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter

References (40)

1. E. Alba and B. Dorronsoro. Cellular Genetic Algorithms. Operations Research/Computer Science Interfaces Series, Vol. 42. Springer-Verlag, Heidelberg, Germany, 2008.
2. E. Alba and M. Tomassini. Parallelism and evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 6(5):443-462, 2002.
3. E. Alba, B. Dorronsoro, and H. Alfonso. Cellular memetic algorithms. Journal of Computer Science and Technology, 5(4):257-263, 2006.
4. E. Alba, B. Dorronsoro, M. Giacobini, and M. Tomassini. Decentralized cellular evolutionary algorithms. In Handbook of Bioinspired Algorithms and Applications, CRC Press, Boca Raton, FL, pp. 103-120,2006.
5. L. Benini, A. Bogliolo, R. Bogliolo, and G.D. Micheli. A survey of design techniques for system-level dynamic power management. IEEE Transactions on VLSI Systems, 8:299-316, 2000.
6. T.D. Burd, T.A. Pering, A.J. Stratakos, and R.W. Brodersen. A dynamic voltage scaled microprocessor system. IEEE Journal Solid-State Circuits, 35(11):1571-1580, 2000.
7. A.P. Chandrakasan and R.W. Brodersen. Low Power Digital CMOS Design. Kluwer Academic Publisher, Boston, MA, 1995.
8. C.A. Coello, D.A. Van Veldhuizen, and G.B. Lamont. Evolutionary Algorithms for Solving MultiObjective Problems. Genetic Algorithms and Academic Publisher, Evolutionary Computation. Kluwer Dordrecht, the Netherlands, 2002.
9. K. Deb. Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley andamp; Sons, New York, 2001.
10. E. Deelman, G. Singh, M.H. Su, J. Blythe, A. Gil, C. Kesselman, G. Mehta, K. Vahi, G.B. Berriman, J. Good, A. Laity, J.C. Jacob, and D.S. Katz. Pegasus: A framework for mapping complex scientific workflows onto distributed systems. Scientific Programming Journal, 13:219-237, 2005.
11. E. Falkenauer. Genetic Algorithms and Grouping Problems. John Wiley andamp; Sons Ltd., London, 1999.
12. M. Guzek, J.E. Pecero, B. Dorronsoro, and P. Bouvry. A cellular genetic algorithm for scheduling applications and energy-aware communication optimization. In Workshop on Optimization Issues in Energy Efficient Distributed Systems (OPTIM), Part of the International Conference on High Performance Computing andamp; Simulation (HPCS), Caen, France, pp. 241-248, 2010.
13. J.J. Hwang, Y.-C. Chow, F.D. Angers, and C.-Y. Lee. Scheduling precedence graphs in systems with interprocessor communication times. SIAM Journal on Computing, 18(2):244-257,1989.
14. S. Irani, S. Shukla, and R. Gupta. Online strategies for dynamic power management in system with multiple power-saving states. ACM Transactions on Embedded Computing Systems, 2(3):325-346, 2003.
15. S.U. Khan and I. Ahmad. A cooperative game theoretical technique for joint optimization of energy consumption and response time in computational grids. IEEE Transactions on Parallel and Distributed Systems, 20(3):346-360, 2009.
16. Y.K. Kwok and I. Ahmad. Benchmarking and comparison of the task graph scheduling algorithms. Journal of Parallel and Distributed Computing, 59(3):381-422,1999.
17. Y.K. Kwok and I. Ahmad. Static scheduling algorithms for allocating directed task graphs to multiprocessors. ACM Computing Surveys, 31(4):406-471,1999.
18. Y.C. Lee and A.Y. Zomaya. Minimizing energy consumption for precedence-constrained applications using dynamic voltage scaling. In Ninth IEEE/ACM International Symposium on Cluster Computing and the Grid, IEEE Computer Society, Washington, DC, pp. 92-99, 2009.
19. Y.C. Lee and A.Y. Zomaya. Energy efficient utilization of resources in cloud computing systems. Journal of Supercomputing, 1-13, DOI: 10.1007/s11227-010-0421-3, 2011.
20. R. Lepère and D. Trystram. A new clustering algorithm for large communication delays. In Proceedings of the 16th International Parallel and Distributed Processing Symposium, IPDPS’02, IEEE Computer Society, Fort Lauderdale, FL, pp. 68-73, April 2002.
21. G. Magklis, G. Semeraro, D.H. Albonesi, S.G. Dropsho, S. Dwarkadas, and M.L. Scott. Dynamic frequency and voltage scaling for a multiple-clock-domain microprocessor. IEEE Micro, 23:62-68, 2003.
22. A. Mahjoub, J.E. Pecero, and D. Trystram. Scheduling with uncertainties on new computing platforms. Journal Computational Optimization and Applications, 48(2):369-398, 2011, DOI: 10.1007/s10589-009-9311-0.
23. B. Manderick and P. Spiessens. Fine-grained parallel genetic algorithm. In J.D. Schaffer, ed., Proceedings of the Third International Conference on Genetic Algorithms (ICGA), Morgan Kaufmann, San Francisco, pp. 428-433,1989.
24. S.M. Martin, K. Flautner, T. Mudge, and D. Blaauw. Combined dynamic voltage scaling and adaptive body biasing for lower power microprocessors under dynamic workloads. In Proceedings of the 2002 IEEE/ACM International Conference on Computer-Aided Design, ICCAD’02, ACM, New York, pp. 721-725, 2002.
25. P. Mejia-Alvarez, E. Levner, and D. Mossé. Adaptive scheduling server for power-aware real-time tasks. ACM Transactions on Embedded Computing Systems, 2:284-306, 2004.
26. V. Nélis and J. Goossens. Mora: An energy-aware slack reclamation scheme for scheduling sporadic real-time tasks upon multiprocessor platforms. In International Conference on Real-Time Computing Systems and Applications, pp. 210-215, 2009.
27. Q.H. Nguyen, Y.-S. Ong, M.-H. Lim, and N. Krasnogor. Adaptive cellular memetic algorithms. Evolutionary Computation, 17(2):231-256, 2009.
28. J.E. Pecero, D. Trystram, and A.Y. Zomaya. A new genetic algorithm for scheduling for large communication delays. In Euro-Par, Delft, the Netherlands, pp. 241-252, 2009.
29. N.B. Rizvandi, J. Taheri, A.Y. Zomaya, and Y.C. Lee. Linear combinations of DVFS-enabled processor frequencies to modify the energy-aware scheduling algorithms. In 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, IEEE, Melbourne, Victoria, Australia, pp. 388-397, 2010.
30. V. Sarkar. Partitioning and Scheduling Parallel Programs for Execution on Multiprocessors. MIT Press, Cambridge, MA, 1989.
31. D.J. Sheskin. Handbook of Parametric and Nonparametric Statistical Procedures. CRC Press, Boca Raton, FL, 2003.
32. O. Sinnen. Task Scheduling for Parallel Systems. Wiley-Interscience, Hoboken, NJ, 2007.
33. R. Subrata, A.Y. Zomaya, and B. Landfeldt. Cooperative power-aware scheduling in grid computing environments. Journal of Parallel and Distributed Computing, 70:84-91, 2010.
34. E.-G Talbi. Metaheuristics: From Design to Implementation. John Wiley andamp; Sons, Hoboken, NJ, 2009.
35. E. Talpes and D. Marculescu. Toward a multiple clock/voltage island design style for power-aware processors. IEEE Transactions on Very Large Scale Integration Systems, 13:591-603, 2005.
36. J.D. Ullman. NP-complete scheduling problems. Journal of Computer and System Sciences, 10(3):384-393, 1975.
37. D. Whitley. Cellular genetic algorithms. In S. Forrest, ed., Proceedings of the Fifth International Conference on Genetic Algorithms (ICGA), Morgan Kaufmann, Urbana-Champaign, IL, p. 658,1993.
38. T. Xie, X. Qin, and M. Nijim. Solving energy-latency dilemma: Task allocation for parallel applications in heterogeneous embedded systems. In Proceedings of the International Conference on Parallel Processing (ICPP ’06), Washington, DC, pp. 12-22, 2006.
39. J.H. Zar. Biostatistical Analysis. Prentice Hall, Upper Saddle River, NJ, 1999.
40. A.Y. Zomaya and G. Chan. Efficient clustering for parallel tasks execution in distributed systems. International Journal of Foundations of Computer Science, 16(2):281-299, 2005.