Joint virtual machine assignment and traffic engineering for green data center networks

Lin Wang, Fa Zhang, Athanasios V. Vasilakos, Chenying Hou, Zhiyong Liu

Research output: Contribution to JournalArticleAcademicpeer-review


The popularization of cloud computing brings emergency concern to the energy consumption in big data centers. Besides the servers, the energy consumed by the network in a data center is also considerable. Existing works for improving the network energy efficiency are mainly focused on traffic engineering, i.e., consolidating flows and switching off unnecessary devices, which fails to comprehensively consider the unique features in data centers. In this paper, we advocate a joint optimization for achieving energy efficiency of data center networks by proposing a unified optimization framework. In this framework, we consider to take advantage of the application characteristics and topology features, and to integrate virtual machine assignment and traffic engineering. Under this framework, we then devise two efficient algorithms, TE VMA and TER, for assigning virtual machines and routing traffic flows respectively. Knowing the communication patterns of the applications, the TE VMA algorithm is purposeful and can generate desirable traffic conditions for the next-step routing optimization. The TER algorithm makes full use of the hierarchical feature of the topology and is conducted on the multipath routing protocol. The performance of the overall framework is confirmed by both theoretical analysis and simulation results, where up to 50% total energy savings can be achieved, 20% more compared with traffic engineering only approaches.

Original languageEnglish
Pages (from-to)107-112
Number of pages6
JournalPerformance Evaluation Review
Issue number3
Publication statusPublished - 1 Jan 2014
Externally publishedYes


  • Data Center Networks
  • Energy Efficiency
  • Traffic Engineering
  • Virtual Machine Assignment


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