Power-Efficient Assignment of Virtual Machines to Physical Machines

  • Jordi Arjona Aroca
  • Antonio Fernández Anta
  • Miguel A. Mosteiro
  • Christopher Thraves
  • Lin Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8907)

Abstract

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 criteria 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.

Keywords

Cloud computing Generalized assignment Scheduling Load balancing Power efficiency 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jordi Arjona Aroca
    • 1
  • Antonio Fernández Anta
    • 2
  • Miguel A. Mosteiro
    • 3
  • Christopher Thraves
    • 4
  • Lin Wang
    • 5
  1. 1.Universidad Carlos III de MadridMadridSpain
  2. 2.Institute IMDEA NetworksMadridSpain
  3. 3.Department of Computer ScienceKean UniversityUnionUSA
  4. 4.CNRS-LAAS and University of Toulouse - LAASTolouseFrance
  5. 5.Institute of Computing TechnologyChinese Academy of Sciences and University of Chinese Academy of SciencesBeijingChina

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