TY - JOUR
T1 - Joint virtual machine assignment and traffic engineering for green data center networks
AU - Wang, Lin
AU - Zhang, Fa
AU - Vasilakos, Athanasios V.
AU - Hou, Chenying
AU - Liu, Zhiyong
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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.
AB - 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.
KW - Data Center Networks
KW - Energy Efficiency
KW - Traffic Engineering
KW - Virtual Machine Assignment
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U2 - 10.1145/2567529.2567560
DO - 10.1145/2567529.2567560
M3 - Article
AN - SCOPUS:84900872555
SN - 0163-5999
VL - 41
SP - 107
EP - 112
JO - Performance Evaluation Review
JF - Performance Evaluation Review
IS - 3
ER -