VMPlanner: Optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers

被引:166
作者
Fang, Weiwei [1 ]
Liang, Xiangmin [1 ]
Li, Shengxin [1 ]
Chiaraviglio, Luca [2 ]
Xiong, Naixue [3 ]
机构
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
[2] Politecn Torino, Dept Elect, I-10129 Turin, Italy
[3] Colorado Tech Univ, Sch Comp Sci, Colorado Springs, CO 80907 USA
基金
美国国家科学基金会;
关键词
Data center; VM placement; Green networking; Energy efficiency; ENERGY EFFICIENCY; MANAGEMENT; INTERNET; SEARCH;
D O I
10.1016/j.comnet.2012.09.008
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, the power costs of cloud data centers have become a practical concern and have attracted significant attention from both industry and academia. Most of the early works on data center energy efficiency have focused on the biggest power consumers (i.e., computer servers and cooling systems), yet without taking the networking part into consideration. However, recent studies have revealed that the network elements consume 10-20% of the total power in the data center, which poses a great challenge to effectively reducing network power cost without adversely affecting overall network performance. Based on the analysis on topology characteristics and traffic patterns of data centers, this paper presents a novel approach, called VMPlanner, for network power reduction in the virtualization-based data centers. The basic idea of VMPlanner is to optimize both virtual machine placement and traffic flow routing so as to turn off as many unneeded network elements as possible for power saving. We formulate the optimization problem, analyze its hardness, and solve it by designing VMPlanner as a stepwise optimization approach with three approximation algorithms. VMPlanner is implemented and evaluated in a simulated environment with traffic traces collected from a data center test-bed, and the experiment results illustrate the efficacy and efficiency of this approach. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:179 / 196
页数:18
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