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Engineering Simulated Evolution for Virtual Machine Assignment Problem

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Abstract

Cloud computing is a rapidly growing services business in today’s IT market. Its sharp growth is producing many challenges for cloud managers. One primary concern is to efficiently manage the cloud resources, i.e., to maximize utilization of hardware with minimum power consumption. Virtual Machine (VM) consolidation is a very helpful approach to achieve these goals. In this context, we investigate the VM assignment problem. We describe the engineering of a nondeterministic iterative heuristic known as Simulated Evolution (SimE) to solve the well-known NP-hard problem of assigning VMs to hardware hosts. A ‘goodness’ function which is related to the target objective of the problem is defined. It guides the moves and helps traverse the search space in an intelligent manner. In the process of evolution, VMs with high goodness value have a smaller probability of getting perturbed, while those with lower goodness value may be reallocated via a compound move. Results are compared with those published in previous studies, and it is found that the proposed approach is efficient both in terms of solution quality and computational time demand.

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References

  1. Zhang Q, Zhani MF, Zhang S , Zhu Q , Boutaba R , Hellerstein JL (2012). In: Proceedings of the 9th International Conference on Autonomic Computing (ACM, 2012), pp. 145–154

  2. Gartner report (2013). http://www.gartner.com/newsroom/id/2352816

  3. Koomey J (2011) Growth in data center electricity use 2005 to 2010. A report by Analytical Press, completed at the request of The New York Times

  4. Beloglazov A (2013) Energy-efficient management of virtual machines in data centers for cloud computing. Ph.D. thesis, Department of Computing and Information Systems, The University Of Melbourne

  5. Technology research - Gartner Inc. (2010). http://www.gartner.com/newsroom/id/1442113

  6. Energy star computers specification (2012). http://www.energystar.gov/sites/default/files/specs//private/ES_Computers_Draft_1_Version_6.0_Specification.pdf

  7. Raghavendra R, Ranganathan P , Talwar V, Wang Z, Zhu (2008). In: ACM SIGARCH Computer Architecture News, vol. 36 (ACM, 2008), vol. 36, pp. 48–59

  8. Bash CE , Patel CD , Sharma RK (2006). In: Thermal and Thermomechanical Phenomena in Electronics Systems, 2006. ITHERM’06. The Tenth Intersociety Conference on (IEEE, 2006), pp. 445–452

  9. Von Laszewski G , Wang L, Younge AJ, He X (2009). In: Cluster Computing and Workshops, 2009. CLUSTER’09. IEEE International Conference on (IEEE, 2009), pp. 1–10

  10. Verma A, Dasgupta G, Nayak TK, De P, Kothari R (2009). In: Proceedings of the 2009 Conference on USENIX Annual Technical Conference (USENIX Association, 2009), pp. 28–28

  11. Chen G, He W, Liu J, Nath S, Rigas L, Xiao L, Zhao F (2008). In: NSDI, vol. 8, pp. 337–350

  12. Fu Y, Lu C, Wang H (2010). In: Parallel & Distributed Processing (IPDPS), IEEE International Symposium on (IEEE, 2010), pp. 1–11

  13. Technology research - Gartner Inc. (2009). http://www.gartner.com/newsroom/id/1234513

  14. Gulati A, Holler A, Ji M, Shanmuganathan G, Waldspurger C, Zhu X (2012) VMware Tech J 1(1):45

    Google Scholar 

  15. Shi L, Furlong J, Wang R (2013). In: Computers and Communications (ISCC), 2013 IEEE Symposium on (IEEE, 2013), pp. 000,009–000,015

  16. Gao Y, Guan H, Qi Z, Hou Y, Liu L (2013) J Comput Syst Sci 79(8):1230

    Article  MathSciNet  Google Scholar 

  17. Xu J, Fortes JA (2010). In: Green Computing and Communications (GreenCom), 2010 IEEE/ACM Int’l Conference on & Int’l Conference on Cyber, Physical and Social Computing (CPSCom) (IEEE, 2010), pp. 179–188

  18. Panigrahy R, Talwar K, Uyeda L, Wieder U (2011) Heuristics for vector bin packing. research. microsoft. com

  19. Ajiro Y, Tanaka A (2007). In: Int. CMG Conference, pp. 399–406

  20. Breitgand D, Epstein A (2012) INFOCOM, . In: Proceedings IEEE (IEEE, 2012), pp. 2861–2865

  21. Masson R, Vidal T, Michallet J, Penna PHV, Petrucci V, Subramanian A, Dubedout H (2013) Expert Syst Appl 40(13):5266

    Article  Google Scholar 

  22. Kramer HH, Petrucci V, Subramanian A, Uchoa E, Comput Ind Eng (2012) 63(3):652

  23. Doddavula SK, Kaushik M, Jain A (2011)

  24. Jhawar R, Piuri V, Samarati P (2012). In: CSE, pp. 170–177

  25. Shi L, Butler B, Botvich D, Jennings B (2013). In: Integrated Network Management (IM 2013), 2013 IFIP/IEEE International Symposium on (IEEE, 2013), pp. 499–505

  26. Kling RM, Banerjee P (1987). In: Proceedings of the 24th ACM/IEEE Design Automation Conference (ACM, 1987), pp. 60–66

  27. Sait SM, Youssef H (1999) Iterative Computer Algorithms with Applications in Engineering: Solving Combinatorial Optimization Problems (IEEE Computer Society Press)

  28. Sait SM, Youssef H (1994) VISI physical design automation: Theory and practice. McGraw-Hill, New York

    Google Scholar 

  29. Hartmann A (2005) Phase transitions in combinatorial optimization problems - Basics, Algorithms and Statistical Mechanics. Wiley-VCH, New York

    Book  Google Scholar 

Download references

Acknowledgments

The authors acknowledge King Fahd University of Petroleum & Minerals (KFUPM) for all support. The work was conducted as part of project COE-572132-1. Special thanks to Ms. Fathima Chinoy and Dr. Blair Paul Bremberg for their help in editing and improving the quality of the manuscript.

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Authors and Affiliations

  1. Department of Computer Engineering and Center for Communications and IT Research, Research Institute King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia

    Sadiq M. Sait

  2. Department of Computer Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia

    Kh. Shahzada Shahid

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  1. Sadiq M. Sait
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Correspondence to Sadiq M. Sait.

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Sait, S.M., Shahid, K.S. Engineering Simulated Evolution for Virtual Machine Assignment Problem. Appl Intell 43, 296–307 (2015). https://doi.org/10.1007/s10489-014-0634-x

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