Power-efficient assignment of virtual machines to physical machines

doi:10.1016/j.future.2015.01.006

	Power-efficient assignment of virtual machines to physical machines
	Arjona Aroca, Jordi 2; Fernandez Anta, Antonio 1; Mosteiro, Miguel A.3; Thraves, Christopher 4,5; Wang, Lin 6,7
	2016
发表期刊	FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
ISSN	0167-739X
卷号	54 页码:82-94
摘要	Motivated by current trends in cloud computing, we study a version of the generalized assignment problem where a set of virtual processors has to be implemented by a set of identical processors. For literature consistency, we say that a set of virtual machines (VMs) is assigned to a set of physical machines (PMs). The optimization criterion is to minimize the power consumed by all the PMs. We term the problem Virtual Machine Assignment (VMA). Crucial differences with previous work include a variable number of PMs, that each VM must be assigned to exactly one PM (i.e., VMs cannot be implemented fractionally), and a minimum power consumption for each active PM. Such infrastructure may be strictly constrained in the number of PMs or in the PMs' capacity, depending on how costly (in terms of power consumption) it is to add a new PM to the system or to heavily load some of the existing PMs. Low usage or ample budget yields models where PM capacity and/or the number of PMs may be assumed unbounded for all practical purposes. We study four VMA problems depending on whether the capacity or the number of PMs is bounded or not. Specifically, we study hardness and online competitiveness for a variety of cases. To the best of our knowledge, this is the first comprehensive study of the VMA problem for this cost function. (c) 2015 Elsevier B.V. All rights reserved.
关键词	Cloud computing Generalized assignment Scheduling Load balancing
DOI	10.1016/j.future.2015.01.006
收录类别	SCI
语种	英语
资助项目	Comunidad de Madrid[S2009TIC-1692] ; Comunidad de Madrid[S2013/ICE-2894] ; MINECO[TEC2011-29688-C02-01] ; National Natural Science Foundation of China[61020106002] ; National Science Foundation[CCF-1114930] ; Kean University UFRI grant[UFRI1415]
WOS研究方向	Computer Science
WOS类目	Computer Science, Theory & Methods
WOS记录号	WOS:000368383200007
出版者	ELSEVIER SCIENCE BV
引用统计	被引频次：25[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/8919
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Arjona Aroca, Jordi
作者单位	1.Inst IMDEA Networks, Madrid, Spain 2.Univ Carlos III Madrid, Madrid, Spain 3.Kean Univ, Dept Comp Sci, Union, NJ USA 4.CNRS LAAS, Toulouse, France 5.Univ Toulouse LAAS, Toulouse, France 6.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 7.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Arjona Aroca, Jordi,Fernandez Anta, Antonio,Mosteiro, Miguel A.,et al. Power-efficient assignment of virtual machines to physical machines[J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE,2016,54:82-94.
APA	Arjona Aroca, Jordi,Fernandez Anta, Antonio,Mosteiro, Miguel A.,Thraves, Christopher,&Wang, Lin.(2016).Power-efficient assignment of virtual machines to physical machines.FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE,54,82-94.
MLA	Arjona Aroca, Jordi,et al."Power-efficient assignment of virtual machines to physical machines".FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 54(2016):82-94.