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Virtual machine consolidated placement based on multi-objective biogeography-based optimization

delete2016-01-01
delete122
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OA
AI
Q
Qinghua Zheng
R
Rui Li
X
Xiuqi Li
N
Nazaraf Shah
J
Jianke Zhang
田锋 封面图
田锋 (Feng Tian) *
K
Kuo‐Ming Chao
J
Jia Li
DOI:10.1016/j.future.2015.02.010delete
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摘要

摘要

En 中文
Virtual machine placement (VMP) is an important issue in selecting most suitable set of physical machines (PMs) for a set of virtual machines (VMs) in cloud computing environment. VMP problem consists of two sub problems: incremental placement (VMiP) problem and consolidated placement (VMcP) problem. The goal of VMcP is to consolidate the VMs to more suitable PMs. The challenge in VMcP problem is how to find optimal solution effectively and efficiently especially when VMcP is a kind of NP-hard problem. In this paper, we present a novel solution to the VMcP problem called VMPMBBO. The proposed VMPMBBO treats VMcP problem as a complex system and utilizes the biogeography-based optimization (BBO) technique to optimize the virtual machine placement that minimizes both the resource wastage and the power consumption at the same time. Extensive experiments have been conducted using synthetic data from related literature and data from two real datasets. First of all, the necessity of VMcP has been proved by experimental results obtained by applying VMPMBBO. Then, the proposed method is compared with two existing multi-objective VMcP optimization algorithms and it is shown that VMPMBBO has better convergence characteristics and is more computationally efficient as well as robust. And then, the issue of parameter setting of the proposed method has been discussed. Finally, adaptability and extensibility of VMPMBBO have also been proved through experimental results. To the best of our knowledge, this work is the first approach that applies biogeography-based optimization (BBO) to virtual machine placement. (c) 2015 Elsevier B.V. All rights reserved.
Keyword:
Virtual machine placement
Multi-objective optimization
Resource utilization
Biogeography-based optimization
Cloud computing
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期刊

F
Future Generation Computer Systems-The International Journal of eScience
IF:
6.1
论文数:
6.9K
被引数:
2.3W

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X
xi'an jiaotong university
学者数:
9.3W
论文数: 6.7W
被引数: 75
U
university of north carolina
学者数:
7.4W
论文数: 6.5W
被引数: 93
University of North Carolina at Pembroke 封面图
University of North Carolina at Pembroke
学者数:
107
论文数: 125
被引数: 196
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