Exploring mixed integer programming reformulations for virtual machine placement with disk anti-colocation constraints

One of the important problems for datacenter resource management is to place virtual machines (VMs) to physical machines (PMs) such that certain cost, profit or performance objective is optimized, subject to various constraints. In this paper, we consider an interesting and difficult VM placement pr...

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Vydáno v:Performance evaluation Ročník 135; s. 102035
Hlavní autoři: Zheng, Xiaoying, Xia, Ye
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.11.2019
Témata:
Cloud computing
Datacenter
Mixed integer programming
Resource management
Virtual machine placement
Datacenter
Cloud computing
Mixed integer programming
Resource management
Virtual machine placement
ISSN:0166-5316, 1872-745X
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Shrnutí:One of the important problems for datacenter resource management is to place virtual machines (VMs) to physical machines (PMs) such that certain cost, profit or performance objective is optimized, subject to various constraints. In this paper, we consider an interesting and difficult VM placement problem with disk anti-colocation constraints: a VM’s virtual disks should be spread out across the physical disks of its assigned PM. For solutions, we use the mixed integer programming (MIP) formulations and algorithms. However, a challenge is the potentially long computation time of the MIP algorithms. In this paper, we explore how reformulation of the problem can help to reduce the computation time. We develop two reformulations, by redefining the variables, for our VM placement problem and evaluate the computation time of all three formulations. We show that they have vastly different computation time. All three formulations can be useful, but for different problem instances. They all should be kept in the toolbox for tackling the problem. Out of the three, formulation COMB is especially flexible and versatile, and it can solve large problem instances. •A VM’s virtual disks should be spread out across the physical disks•Explore how reformulation of the problem can help to reduce the computation time•All three formulations can be useful, but for different problem instances•Formulation COMB is flexible and versatile, and it can solve large problem instances
ISSN:0166-5316
1872-745X
DOI:10.1016/j.peva.2019.102035