A greedy power-aware routing algorithm for software-defined networks

M. Awad, Yousef Rafique, S. Alhadlaq, Dunya Hassoun, A. Alabdulhadi, S. Thani
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引用次数: 9

Abstract

We consider the problem of minimizing the routing power consumption in software-defined networks. The network is composed of software-defined networking (SDN) nodes and a central controller where routing decisions are centralized. More specifically, the central controller minimizes the routing power consumption by routing flows on the minimum number of active links with the lowest discrete link rates. Thus, it maximizes the number of inactive links and the level of link rates, which reflects significant saving in power consumption. This problem is a mixed-integer programming problem and known to be NP-hard. Therefore, we propose a low-complexity greedy heuristic to minimize the number of active links and link rates by rerouting flows and aggregating them on common links. Numerical results show that the proposed algorithm achieves 17.18% to 32.97% power saving in real network topologies relative to a base shortest path algorithm. The savings are achieved with minimal increase in average path length that is less than 0.2 hops.
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一种用于软件定义网络的贪婪功率感知路由算法
研究了软件定义网络中路由功耗最小化的问题。该网络由软件定义网络(SDN)节点和集中路由决策的中央控制器组成。更具体地说,中央控制器通过在最小数量的活动链路上以最低的离散链路速率路由流来最小化路由功耗。因此,它最大化了非活动链路的数量和链路速率的水平,这反映了功耗的显著节省。这个问题是一个混合整数规划问题,被称为np困难问题。因此,我们提出了一种低复杂度的贪婪启发式算法,通过重路由流并将它们聚集在公共链路上来最小化活动链路的数量和链路速率。数值计算结果表明,在实际网络拓扑中,该算法比基础最短路径算法节能17.18% ~ 32.97%。这种节省是在平均路径长度的最小增加(小于0.2跳)的情况下实现的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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