Engineering Simulated Evolution for Virtual Machine Assignment Problem
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 (...
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| Veröffentlicht in: | Applied intelligence (Dordrecht, Netherlands) Jg. 43; H. 2; S. 296 - 307 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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New York
Springer US
01.09.2015
Springer Nature B.V |
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| ISSN: | 0924-669X, 1573-7497 |
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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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| AbstractList | 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. |
| Author | Shahid, Kh. Shahzada Sait, Sadiq M. |
| Author_xml | – sequence: 1 givenname: Sadiq M. surname: Sait fullname: Sait, Sadiq M. email: sadiq@kfupm.edu.sa organization: Department of Computer Engineering and Center for Communications and IT Research, Research Institute King Fahd University of Petroleum & Minerals – sequence: 2 givenname: Kh. Shahzada surname: Shahid fullname: Shahid, Kh. Shahzada organization: Department of Computer Engineering, King Fahd University of Petroleum & Minerals |
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| CitedBy_id | crossref_primary_10_1007_s10489_018_1264_5 crossref_primary_10_1007_s10586_022_03550_1 crossref_primary_10_1109_ACCESS_2019_2911914 crossref_primary_10_1109_ACCESS_2024_3420173 crossref_primary_10_1007_s10489_016_0774_2 |
| Cites_doi | 10.1016/j.jcss.2013.02.004 10.1145/37888.37897 10.1109/INFCOM.2012.6195716 10.1016/j.cie.2011.07.023 10.1002/3527606734 10.1016/j.eswa.2013.03.037 |
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| DOI | 10.1007/s10489-014-0634-x |
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| Keywords | Nondeterministic algorithms NP-hard Evolutionary metaheuristic Combinatorial optimization Virtual machine placement Simulated evolution |
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| References | MassonRVidalTMichalletJPennaPHVPetrucciVSubramanianADubedoutHExpert Syst Appl20134013526610.1016/j.eswa.2013.03.037 Sait SM, Youssef H (1999) Iterative Computer Algorithms with Applications in Engineering: Solving Combinatorial Optimization Problems (IEEE Computer Society Press) Breitgand D, Epstein A (2012) INFOCOM, . In: Proceedings IEEE (IEEE, 2012), pp. 2861–2865 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 Technology research - Gartner Inc. (2010). http://www.gartner.com/newsroom/id/1442113 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 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 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 HartmannAPhase transitions in combinatorial optimization problems - Basics, Algorithms and Statistical Mechanics2005New YorkWiley-VCH10.1002/3527606734 GaoYGuanHQiZHouYLiuLJ Comput Syst Sci20137981230307921710.1016/j.jcss.2013.02.004 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 Panigrahy R, Talwar K, Uyeda L, Wieder U (2011) Heuristics for vector bin packing. research. microsoft. com Fu Y, Lu C, Wang H (2010). In: Parallel & Distributed Processing (IPDPS), IEEE International Symposium on (IEEE, 2010), pp. 1–11 SaitSMYoussefHVISI physical design automation: Theory and practice1994New YorkMcGraw-Hill Kramer HH, Petrucci V, Subramanian A, Uchoa E, Comput Ind Eng (2012) 63(3):652 Energy star computers specification (2012). http://www.energystar.gov/sites/default/files/specs//private/ES_Computers_Draft_1_Version_6.0_Specification.pdf Chen G, He W, Liu J, Nath S, Rigas L, Xiao L, Zhao F (2008). In: NSDI, vol. 8, pp. 337–350 Shi L, Furlong J, Wang R (2013). In: Computers and Communications (ISCC), 2013 IEEE Symposium on (IEEE, 2013), pp. 000,009–000,015 Doddavula SK, Kaushik M, Jain A (2011) Gartner report (2013). http://www.gartner.com/newsroom/id/2352816 Ajiro Y, Tanaka A (2007). In: Int. CMG Conference, pp. 399–406 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 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 Technology research - Gartner Inc. (2009). http://www.gartner.com/newsroom/id/1234513 Kling RM, Banerjee P (1987). In: Proceedings of the 24th ACM/IEEE Design Automation Conference (ACM, 1987), pp. 60–66 Jhawar R, Piuri V, Samarati P (2012). In: CSE, pp. 170–177 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 GulatiAHollerAJiMShanmuganathanGWaldspurgerCZhuXVMware Tech J20121145 Raghavendra R, Ranganathan P , Talwar V, Wang Z, Zhu (2008). In: ACM SIGARCH Computer Architecture News, vol. 36 (ACM, 2008), vol. 36, pp. 48–59 634_CR11 634_CR10 634_CR15 634_CR13 634_CR12 634_CR19 634_CR18 634_CR17 Y Gao (634_CR16) 2013; 79 634_CR1 A Gulati (634_CR14) 2012; 1 634_CR2 634_CR3 634_CR4 634_CR5 634_CR6 634_CR7 634_CR8 634_CR9 634_CR22 634_CR20 R Masson (634_CR21) 2013; 40 634_CR26 634_CR25 634_CR24 634_CR23 634_CR27 A Hartmann (634_CR29) 2005 SM Sait (634_CR28) 1994 |
| References_xml | – reference: Jhawar R, Piuri V, Samarati P (2012). In: CSE, pp. 170–177 – reference: 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 – reference: 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 – reference: SaitSMYoussefHVISI physical design automation: Theory and practice1994New YorkMcGraw-Hill – reference: Technology research - Gartner Inc. (2009). http://www.gartner.com/newsroom/id/1234513 – reference: GulatiAHollerAJiMShanmuganathanGWaldspurgerCZhuXVMware Tech J20121145 – reference: 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 – reference: GaoYGuanHQiZHouYLiuLJ Comput Syst Sci20137981230307921710.1016/j.jcss.2013.02.004 – reference: 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 – reference: 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 – reference: Shi L, Furlong J, Wang R (2013). In: Computers and Communications (ISCC), 2013 IEEE Symposium on (IEEE, 2013), pp. 000,009–000,015 – reference: HartmannAPhase transitions in combinatorial optimization problems - Basics, Algorithms and Statistical Mechanics2005New YorkWiley-VCH10.1002/3527606734 – reference: 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 – reference: MassonRVidalTMichalletJPennaPHVPetrucciVSubramanianADubedoutHExpert Syst Appl20134013526610.1016/j.eswa.2013.03.037 – reference: Ajiro Y, Tanaka A (2007). In: Int. CMG Conference, pp. 399–406 – reference: Energy star computers specification (2012). http://www.energystar.gov/sites/default/files/specs//private/ES_Computers_Draft_1_Version_6.0_Specification.pdf – reference: 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 – reference: Technology research - Gartner Inc. (2010). http://www.gartner.com/newsroom/id/1442113 – reference: Kramer HH, Petrucci V, Subramanian A, Uchoa E, Comput Ind Eng (2012) 63(3):652 – reference: Fu Y, Lu C, Wang H (2010). In: Parallel & Distributed Processing (IPDPS), IEEE International Symposium on (IEEE, 2010), pp. 1–11 – reference: Gartner report (2013). http://www.gartner.com/newsroom/id/2352816 – reference: Panigrahy R, Talwar K, Uyeda L, Wieder U (2011) Heuristics for vector bin packing. research. microsoft. com – reference: Breitgand D, Epstein A (2012) INFOCOM, . In: Proceedings IEEE (IEEE, 2012), pp. 2861–2865 – reference: Sait SM, Youssef H (1999) Iterative Computer Algorithms with Applications in Engineering: Solving Combinatorial Optimization Problems (IEEE Computer Society Press) – reference: Chen G, He W, Liu J, Nath S, Rigas L, Xiao L, Zhao F (2008). In: NSDI, vol. 8, pp. 337–350 – reference: 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 – reference: Kling RM, Banerjee P (1987). In: Proceedings of the 24th ACM/IEEE Design Automation Conference (ACM, 1987), pp. 60–66 – reference: Doddavula SK, Kaushik M, Jain A (2011) – reference: 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 – volume: 79 start-page: 1230 issue: 8 year: 2013 ident: 634_CR16 publication-title: J Comput Syst Sci doi: 10.1016/j.jcss.2013.02.004 – volume-title: VISI physical design automation: Theory and practice year: 1994 ident: 634_CR28 – ident: 634_CR17 – ident: 634_CR15 – ident: 634_CR13 – ident: 634_CR11 – ident: 634_CR7 – ident: 634_CR24 – ident: 634_CR5 – ident: 634_CR19 – ident: 634_CR9 – ident: 634_CR26 doi: 10.1145/37888.37897 – ident: 634_CR1 – ident: 634_CR3 – ident: 634_CR20 doi: 10.1109/INFCOM.2012.6195716 – ident: 634_CR10 – volume: 1 start-page: 45 issue: 1 year: 2012 ident: 634_CR14 publication-title: VMware Tech J – ident: 634_CR12 – ident: 634_CR8 – ident: 634_CR23 – ident: 634_CR18 – ident: 634_CR6 – ident: 634_CR2 – ident: 634_CR22 doi: 10.1016/j.cie.2011.07.023 – volume-title: Phase transitions in combinatorial optimization problems - Basics, Algorithms and Statistical Mechanics year: 2005 ident: 634_CR29 doi: 10.1002/3527606734 – ident: 634_CR27 – ident: 634_CR4 – ident: 634_CR25 – volume: 40 start-page: 5266 issue: 13 year: 2013 ident: 634_CR21 publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2013.03.037 |
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| SubjectTerms | Algorithms Artificial Intelligence Assignment problem Cloud computing Computer centers Computer engineering Computer peripherals Computer Science Cost control Demand Energy consumption Hardware Heuristic Intelligence Load Machines Manufacturing Markets Mathematical models Mechanical Engineering Operating systems Optimization Packing problem Processes Searching Simulated evolution Software services Virtual environments Workloads |
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| Title | Engineering Simulated Evolution for Virtual Machine Assignment Problem |
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