Eliminating hot-spots based on cold-spot virtual machine migration in the cloud

doi:10.16511/j.cnki.qhdxxb.2016.26.017

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Abstract Initial allocations of virtual machine(VM) resources are often unable to meet the performance requirements of runtime services, resulting in excessive resource utilization, slow response times and other "hot spot" problems. The traditional approach to eliminating these hot-spots has mainly been to include resources extensions and virtual machine live migration, but there are still problems with insufficient resources and large migration costs. The paper describes a hot-spot elimination method based on cold-spot VMs which migrates the cold-spot VM and then distributes the released resources to the hot-spot VM. This approach maintains the hot-spot service performance and reduces the cost of hot-spot elimination to better meet the SLA constraints. Tests show that this method is feasible and effective.

Keywords live migration hot-spot eliminating cold-spot virtual machine service-level agreement

ZTFLH:

TP311.5

Issue Date: 15 November 2016

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	GUO Jun
	YAN Yongming
	MA Anxiang
	ZHANG Bin

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GUO Jun,YAN Yongming,MA Anxiang, et al. Eliminating hot-spots based on cold-spot virtual machine migration in the cloud[J]. Journal of Tsinghua University(Science and Technology), 2016, 56(11): 1232-1236.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2016.26.017 OR http://jst.tsinghuajournals.com/EN/Y2016/V56/I11/1232

[1]	Mishra M, Das A, Kulkarni P, et al. Dynamic resource management using virtual machine migrations[J]. IEEE Communications Magazine, 2012, 50(9):34-40.
[2]	Wood T, Shenoy P, Venkataramani A, et al. Sandpiper:Black-box and gray-box resource management for virtual machines[J]. Computer Networks, 2009, 53(17):2923-2938.
[3]	ZHAN Zhihui, LIU Xiaofang, GONG Yuejiao, et al. Cloud computing resource scheduling and a survey of its evolutionary approaches[J]. ACM Computing Surveys, 2015, 47(4):1-33.
[4]	LIU Yanbing, GONG Bo, XING Congcong, et al. A virtual machine migration strategy based on time series workload prediction using cloud model[J]. Mathematical Problems in Engineering, 2014, 2014:1-11.
[5]	Rosa L, Rodrigues L, Lopes A, et al. Self-management of adaptable component-based applications[J]. IEEE Transactions on Software Engineering, 2013, 39(3):403-421.
[6]	YE Kejiang, JIANG Xiaohong, HUANG Dawei, et al. Live migration of multiple virtual machines with resource reservation in cloud computing environments[C]//2011 IEEE International Conference on Cloud Computing (CLOUD). Washington, D.C., USA:IEEE Press, 2011:267-274.
[7]	赵秀涛, 张斌, 张长胜. 一种基于服务选取的SBS云资源优化分配方法[J]. 软件学报, 2015, 26(4):867-885.ZHAO Xiutao, ZHANG Bin, ZHANG Changsheng. Service selection based resource alloication for SBS in cloud environments[J]. Journal of Software, 2015, 26(4):867-885. (in Chinese) url: http://www.cnki.com.cn/Article/CJFDTotal-DBDX201301008.htm
[8]	JIN Hai, GAO Wei, WU Song, et al. Optimizing the live migration of virtual machine by CPU scheduling[J]. Journal of Network and Computer Applications, 2011, 34(4):1088-1096.
[9]	Shribman A, Hudzia B. Pre-copy and post-copy VM live migration for memory intensive applications[C]//European Conference on Parallel Processing. Rhodes Islands:Greece Springer-Verlag, 2012:539-547.
[10]	ZHANG Wei, ZHU Mingfa, GONG Tao, et al. Performance degradation-aware virtual machine live migration in virtualized servers[C]//13th International Conference on Parallel and Distributed Computing, Applications and Technologies. Beijing, China:IEEE Press, 2012:429-435.
[11]	Strunk A. Costs of virtual machine live migration:A survey[C]//IEEE Eighth World Congress on Services. Honolulu, HI:IEEE Press, 2012:323-329.
[12]	Sagana C, Geetha M, Suganthe R. Performance enhancement in live migration for cloud computing environments[C]//International Conference on Information Communication and Embedded Systems (ICICES). Chennai, Indian:IEEE Press, 2013:361-366.
[13]	闫永明, 张斌, 郭军, 等. 基于模糊层次分析的虚拟机热度综合评估方法[J]. 东北大学学报:自然科学版, 2015, 36(2):182-187.YAN Yongming, ZHANG Bin, GUO Jun, et al. Virtual machine hotspot degree comprehensive evaluation method based on fuzzy analytic hierarchy process[J]. Journal of Northeastern University(Natural Science), 2015, 36(2):182-187. (in Chinese)

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