Abstract
Dynamic consolidation of virtual machines (VMs) in a data center is an effective way to reduce the energy consumption and improve physical resource utilization. Determining which VMs should be migrated from an overloaded host directly influences the VM migration time and increases energy consumption for the whole data center, and can cause the service level of agreement (SLA), delivered by providers and users, to be violated. So when designing a VM selection policy, we not only consider CPU utilization, but also define a variable that represents the degree of resource satisfaction to select the VMs. In addition, we propose a novel VM placement policy that prefers placing a migratable VM on a host that has the minimum correlation coefficient. The bigger correlation coefficient a host has, the greater the influence will be on VMs located on that host after the migration. Using CloudSim, we run simulations whose results let draw us to conclude that the policies we propose in this paper perform better than existing policies in terms of energy consumption, VM migration time, and SLA violation percentage.
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Zhu X, Young D, Watson B J, Wang Z, Rolia J, Singhal S, McKee B, Hyser C, Gmach D, Gardner R, Christian T, Cherkasova L. 1000 islands: an integrated approach to resource management for virtualized data centers. Cluster Computing, 2009, 12(1): 45–57
Greenberg A, Hamilton J, Maltz D A, Patel P. The cost of a cloud: research problems in data center networks. ACM SIGCOMM Computer Communication Review, 2008, 39(1): 68–73
Dong J, Jin X, Wang H, Li Y, Zhang P, Cheng S. Energy-saving virtual machine placement in Cloud data centers. In: Proceedings of the 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid). 2013, 618–624
Barroso L A, Hölzle U. The datacenter as a computer: an introduction to the design of warehouse-scale machines. Synthesis lectures on computer architecture, 2009, 4(1): 1–108
Nathuji R, Schwan K. Virtualpower: coordinated power management in virtualized enterprise systems. ACM SIGOPS Operating Systems Review, 2007, 41(6): 265–278
Kusic D, Kephart J, Hanson J, Kandasamy N, Jiang G. Power and performance management of virtualized computing environments via lookahead control. Cluster Computing, 2009, 12(1): 1–15
Verma A, Ahuja P, Neogi A. pMapper: power and migration cost aware application placement in virtualized systems. In: Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware. 2008, 243–264
Srikantaiah S, Kansal A, Zhao F. Energy aware consolidation for cloud computing. In: Proceedings of USENIX Workshop on Power Aware Computing and Systems in conjunction with OSDI. 2008, 1–5
Zhu X, Young D, Watson B J, Wang Z, Rolia J, Singhal S, McKee, Hyser C, Gmach D, Gardner T, Cherkasova L. 1000 Islands: integrated capacity and workload management for the next generation data center. In: Proceedings of the 5th International Conference Autonomic Computing (ICAC). 2008, 172–181
Gmach D, Rolia J, Cherkasova L, Belrose G, Turicchi T, Kemper A. An integrated approach to resource pool management: policies, efficiency and quality metrics. In: Proceedings of IEEE 38th International Conference Dependable Systems and Networks (DSN). 2008, 326–335
Beloglazov A, Buyya R. Adaptive threshold-based approach for energy-efficient consolidation of virtual machines in Cloud data centers. In: Proceedings of the 8th International Workshop on Middleware for Grids, Clouds and e-Science. 2010: 4
Calheiros R N, Buyya R, Beloglazov A, Rose CAFD, Buyya R. CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience, 2011, 41(1): 23–50
Beloglazov A, Buyya R. Optimal online deterministic algorithms and adaptive Heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers. Concurrency and Computation: Practice and Experience, 2012, 24(12): 1397–1420
Cao Z, Dong S. Dynamic VM consolidation for energy-aware and SLA violation reduction in cloud Computing. In: Proceedings of the 13th International Conference on Parallel and Distributed Computing, Applications and Technologies. 2012, 363–369
Bobroff N, Kochut A, Beaty K. Dynamic placement of virtual machines for managing SLA violations. In: Proceedings of the 10th IFIP/IEEE International Symposium on Integrated Network Management. 2007, 119–128
Wood T, Shenoy P, Venkataramani A, Yousif M. Black-box and graybox strategies for virtual machine migration. In: Proceedings of the 4th USENIX Symposium on Networked Systems Design and Implementation. 2007, 229–242
Fan X, Weber WD, Barroso LA. Power provisioning for a warehouse-sized computer. In: Proceedings of the 34th Annual International Symposium on Computer Architecture. 2007, 35(2): 13–23
Beloglazov A, Abawajy J, Buyya R. Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Generation Computer Systems, 2012, 28(5): 755–768
Xu F, Liu F, Liu L, Jin H, Li B. Iaware: making live migration of virtual machines interference-aware in the cloud. IEEE Transactions on Computers, 2014, 63(12): 3012–3025
Song Y, Wang H, Li Y, Feng B, Sun Y. Multi-tiered on-demand resource scheduling for VM-based data center. In: Proceedings of the 9th IEEE/ACM International Symposium on Cluster Computing and the Grid. 2009, 148–155
Calheiros R N, Ranjan R, De Rose C A F, Buyya R. CloudSim: A novel framework for modeling and simulation of cloud computing infrastructures and services. arXiv preprint arXiv, 2009:0903.2525
Fan X, Weber WD, Barroso L A. Power provisioning for a warehousesized computer. ACM SIGARCH Computer Architecture News, 2007, 35(2): 13–23
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Xiong Fu received his BS and PhD in computer science from the University of Science and Technology of China, China, in 2002 and 2007, respectively. He is currently an associate professor in computer science at the Nanjing University of Posts & Telecommunications, China. His research interests include parallel and distributed computing, and cloud computing.
Chen Zhou received her BS in computer science from the Nantong University, Nantong, in 2013. She is a master candidate at Nanjing University of Posts & Telecommunications, China. Her research interests include cloud computing, and computer networks.
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Fu, X., Zhou, C. Virtual machine selection and placement for dynamic consolidation in Cloud computing environment. Front. Comput. Sci. 9, 322–330 (2015). https://doi.org/10.1007/s11704-015-4286-8
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DOI: https://doi.org/10.1007/s11704-015-4286-8