Paper Info
Title
A Multi-Objective Ant Colony System Algorithm for Virtual Machine Placement in Traffic Intense Data Centers.
Abstract
Virtual machine (VM) placement can meet different kinds of performance targets in data centers. As a result, it has become one of the most critical operations in data centers. In this paper, we investigate the VM placement problem for cloud applications, which have intense bandwidth requirements. In this kind of applications, all VMs communicate with a single designated point. The work of predecessors focuses on the revenue of communications in the network, and tries to find a good solution composed of the best fitted VMs. However, in their work, where to place the selected VMs is not important and has no effect on their objective, and this may cause high power consumption. We formulate the problem as a bin packing problem, which is strictly NP-hard. Then, we propose a multi-objective Ant Colony System (ACS) algorithm which is called ACS-BVMP. The goal is to obtain Pareto optimal solution set, which can simultaneously maximize the revenue of communications and minimize the power consumption of PMs. The proposed algorithm is tested with some instances from the literature. Its solution set is compared with two existing multi-objective algorithms and three single-objective algorithms. The results show that our proposed algorithm outperforms the above algorithms.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2875034
IEEE ACCESS
Keywords
Field
DocType
Virtual machine placement,Ant Colony System algorithm,Pareto optimization,traffic intense data center
Revenue,Virtual machine,Computer science,Algorithm,Network topology,Bandwidth (signal processing),Solution set,Ant colony,Bin packing problem,Distributed computing,Cloud computing
Journal
Volume
ISSN
Citations 
6
2169-3536
1
PageRank 
References 
Authors
0.36
0
4
Name
Order
Citations
PageRank
Yao Qin153.50
Hua Wang27614.82
Fangjin Zhu3204.07
Linbo Zhai4157.01