Evolutionary multiobjective optimization for Green clouds

GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion

Volumn , Issue , 2012, Pages 19-26

  Phan, Dung H ^a   Suzuki, Junichi ^a   Carroll, Raymond ^b   Balasubramaniam, Sasitharan ^b   Donnelly, William ^b   Botvich, Dmitri ^b  

^a UNIVERSITY OF MASSACHUSETTS BOSTON   (United States)

^b South East Technological University   (Ireland)

Author keywords

Cloud computing; Evolutionary multiobjective optimization; Internet data centers; Renewable energy; Sustainability

Indexed keywords

CLOUD COMPUTING; ECONOMIC AND SOCIAL EFFECTS; ENERGY UTILIZATION; GREEN COMPUTING; PARETO PRINCIPLE; SUSTAINABLE DEVELOPMENT;

COOLING ENERGY CONSUMPTION; EVOLUTIONARY MULTIOBJECTIVE OPTIMIZATION; INTERNET DATA CENTERS; PARETO OPTIMAL SOLUTIONS; RENEWABLE ENERGIES; RENEWABLE ENERGY CONSUMPTION; SERVICE MIGRATION; SOURCE OF ENERGY;

MULTIOBJECTIVE OPTIMIZATION;

EID: 84865008471     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2330784.2330788     Document Type: Conference Paper

References (27)

1. C. Bash and G. Forman. Cool job allocation: Measuring the power savings of placing jobs at cooling-efficient locations in the data center. In Proc. USENIX Annual Technical Conference, 2007.
2. D. J. Bradley, R. E. Harper, and S. W. Hunter. Workload-based power management for parallel computer systems. IBM J. Res. Dev., 47(5-6), 2003.
3. R. Das, J. O. Kephart, C. Lefurgy, G. Tesauro, D. W. Levine, and H. Chan. Autonomic multi-agent management of power and performance in data centers. In Proc. Int'l Conf. of Autonomic Agents and Multiagent Syst., 2008.
4. K. Deb, S. Agrawal, A. Pratab, and T. Meyarivan. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In Proc. Int'l Conf. on Parallel Problem Solving from Nature, 2000.
5. K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In Proc. Int'l Conf. on Parallel Problem Solving from Nature, 2001.
6. T. V. T. Duy, Y. Sato, and Y. Inoguchi. Performance evaluation of a green scheduling algorithm for energy savings in cloud computing. In Proc. Int'l Parallel and Distributed Processing Symposium, 2010.
7. European Commission. Code of conduct on data centres energy efficiency, version 1.0. 2008.
8. S. K. Garg, C. S. Yeo, A. Anandasivam, and R. Buyya. Environment- conscious scheduling of HPC applications on distributed cloud-oriented data centers. J. Parallel and Dist. Comput., 71(6), 2010.
9. Global Action Plan. Green ICT handbook: A guide to green ICT. 2009.
10. K. H. Kim, A. Beloglazov, and R. Buyya. Power-aware provisioning of virtual machines for real-time cloud services. Concurrency Computat.: Pract. Exper., 23(13), 2011.
11. J. Koomey. Growth in data center electricity use 2005 to 2010. Analytics Press, 2011.
12. C. Malone and C. Belady. Metrics to characterize data center and it equipment energy use. In Proc. Digital Power Forum, 2006.
13. D. Meisner, B. T. Gold, and T. F. Wenisch. Powernap: Eliminating server idle power. In Proc. Int'l Conf. on Architectural Support for Progr. Lang. and Operating Syst., 2009.
14. J. Moore, J. Chase, P. Ranganathan, and R. Sharma. Making scheduling \cool": temperature-aware workload placement in data centers. In Proc. USENIX Annual Technical Conference, 2005.
15. M. J. Moran and H. N. Shapiro. Fundamentals of engineering thermodynamics. Wiley, 1995.
16. C. Patel, R. Sharma, C. Bash, and S. Graupner. Energy aware grid: Global workload placement based on energy efficiency. In Proc. Int'l Mechanical Engineering Congress and Exposition, 2003.
17. A. Qureshi, R. Weber, H. Balakrishnan, J. Guttag, and B. Maggs. Cutting the electric bill for internet-scale systems. In Proc. ACM SIGCOMM Conference, 2009.
18. Renewable Energy Policy Network for the 21st Century (REN21). Renewables 2011: Global status report. 2011.
19. C. Rusu, A. Ferreira, C. Scordino, and A. Watson. Energy-efficient real-time heterogeneous server clusters. In Proc. IEEE Real-Time and Embedded Technology and Applications Symposium, 2006.
20. K. G. Saurabh, S. Y. Chee, and R. Buyya. Green cloud framework for improving carbon efficiency of clouds. In Proc. Int'l Conf. on Parallel Proc., 2011.
21. R. Sharma, C. Bash, C. Patel, R. Friedrich, and J. Chase. Balance of power: Dynamic thermal management for Internet data centers. IEEE Internet Comput., 9(1), 2005.
22. N. Srinivas and K. Deb. Multiobjective function optimization using nondominated sorting genetic algorithms. Evol. Computat., 2(3), 1995.
23. A.-A. Tantar, E. Tantar, and P. Bouvry. Load balancing for sustainable ICT. In Proc. ACM Genetic and Evolutionary Computation Conference, 2011.
24. The. U.S. Environmental Protection Agency (EPA). Report to congress on server and data center energy efficiency public law 109-431. 2007.
25. L. Wang, A. J. Younge, T. R. Furlani, G. von Laszewski, J. Dayal, and X. He. Towards thermal aware workload scheduling in a data center. In Proc. Int'l S. on Pervasive Syst., Algorithms and Netw., 2009.
26. Y. Zeratul and T. Maolin. Penalty-based genetic algorithm for the composite SaaS placement problem in the cloud. In Proc. IEEE Congress on Evol. Computat., 2010.
27. E. Zitzler and L. Thiele. Multiobjective optimization using evolutionary algorithms: A comparative study. In Proc. Int'l Conf. on Parallel Problem Solving from Nature, 1998.