GreenDCN: A General Framework for Achieving Energy Efficiency in Data Center Networks

被引:144
|
作者
Wang, Lin [1 ,2 ,3 ]
Zhang, Fa [1 ,2 ]
Arjona Aroca, Jordi [4 ,5 ]
Vasilakos, Athanasios V. [6 ]
Zheng, Kai [7 ]
Hou, Chenying [1 ,2 ,3 ]
Li, Dan [8 ]
Liu, Zhiyong [9 ]
机构
[1] Chinese Acad Sci, Adv Comp Res Lab, Beijing, Peoples R China
[2] Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China
[3] Univ Chinese Acad Sci, Beijing, Peoples R China
[4] Inst IMDEA Networks, Madrid, Spain
[5] Univ Carlos III Madrid, Madrid, Spain
[6] Univ Western Macedonia, Florina, Greece
[7] IBM China Res Lab, Beijing, Peoples R China
[8] Tsinghua Univ, Dept Comp Sci, Beijing 100084, Peoples R China
[9] Chinese Acad Sci, State Key Lab Comp Architecture, Inst Comp Technol, Beijing, Peoples R China
关键词
Data center networks; energy efficiency; virtual machine assignment; traffic engineering;
D O I
10.1109/JSAC.2014.140102
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The popularization of cloud computing has raised concerns over the energy consumption that takes place in data centers. In addition to the energy consumed by servers, the energy consumed by large numbers of network devices emerges as a significant problem. Existing work on energy-efficient data center networking primarily focuses on traffic engineering, which is usually adapted from traditional networks. We propose a new framework to embrace the new opportunities brought by combining some special features of data centers with traffic engineering. Based on this framework, we characterize the problem of achieving energy efficiency with a time-aware model, and we prove its NP-hardness with a solution that has two steps. First, we solve the problem of assigning virtual machines (VM) to servers to reduce the amount of traffic and to generate favorable conditions for traffic engineering. The solution reached for this problem is based on three essential principles that we propose. Second, we reduce the number of active switches and balance traffic flows, depending on the relation between power consumption and routing, to achieve energy conservation. Experimental results confirm that, by using this framework, we can achieve up to 50 percent energy savings. We also provide a comprehensive discussion on the scalability and practicability of the framework.
引用
收藏
页码:4 / 15
页数:12
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