Energy Management Through Optimized Routing and Device Powering for Greener Communication Networks

被引:67
作者
Addis, Bernardetta [1 ]
Capone, Antonio [2 ]
Carello, Giuliana [2 ]
Gianoli, Luca G. [3 ]
Sanso, Brunilde [3 ]
机构
[1] Univ Turin, Dipartimento Informat, I-10149 Turin, Italy
[2] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, I-20133 Milan, Italy
[3] Ecole Polytech, Dept Genie Elect, Montreal, PQ H3C 3A7, Canada
关键词
Energy saving; flow-based routing; IP networks; multiperiod; network optimization; traffic engineering; FRAMEWORK; ETHERNET;
D O I
10.1109/TNET.2013.2249667
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
080201 [机械制造及其自动化];
摘要
Recent data confirm that the power consumption of the information and communications technologies (ICT) and of the Internet itself can no longer be ignored, considering the increasing pervasiveness and the importance of the sector on productivity and economic growth. Although the traffic load of communication networks varies greatly over time and rarely reaches capacity limits, its energy consumption is almost constant. Based on this observation, energy management strategies are being considered with the goal of minimizing the energy consumption, so that consumption becomes proportional to the traffic load either at the individual-device level or for the whole network. The focus of this paper is to minimize the energy consumption of the network through a management strategy that selectively switches off devices according to the traffic level. We consider a set of traffic scenarios and jointly optimize their energy consumption assuming a per-flow routing. We propose a traffic engineering mathematical programming formulation based on integer linear programming that includes constraints on the changes of the device states and routing paths to limit the impact on quality of service and the signaling overhead. We show a set of numerical results obtained using the energy consumption of real routers and study the impact of the different parameters and constraints on the optimal energy management strategy. We also present heuristic results to compare the optimal operational planning with online energy management operation.
引用
收藏
页码:313 / 325
页数:13
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