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Linear programming approaches for power savings in software-defined networks

机译:软件定义网络中节能的线性规划方法

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Software-defined networks have been proposed as a viable solution to decrease the power consumption of the networking component in data center networks. Still the question remains on which scheduling algorithms are most suited to achieve this goal. We propose 4 different linear programming approaches that schedule requested traffic flows on SDN switches according to different objectives. Depending on pre-defined software quality requirements such as delay and performance, a single variation or a combination of variations can be selected to optimize the power saving and the performance metrics. Our simulation results demonstrate that all our algorithm variations outperform the shortest path scheduling algorithm, our baseline on power savings, less or more strongly depending on the power model chosen. We show that in FatTree networks, where switches can save up to 60% of power in sleeping mode, we can achieve 15% minimum improvement assuming a one-to-one traffic scenario. Two of our algorithm variations privilege performance over power saving and still provide around 45% of the maximum achievable savings.
机译:已经提出了软件定义的网络作为可行的解决方案,以降低数据中心网络中的网络组件的功耗。问题仍然是哪个调度算法最适合实现这一目标。我们提出了4种不同的线性编程方法,根据不同的目标,SDN交换机上的Schedulted的流量流动。根据预定义的软件质量要求,例如延迟和性能,可以选择单个变体或变体组合以优化省电和性能度量。我们的仿真结果表明,我们所有的算法变化都优于最短路径调度算法,我们的基线对功率节省的基准,取决于所选择的功率模型。我们展示了在Fattree网络中,开关可以节省高达60%的睡眠模式,我们可以达到15%的最低改进,假设一对一的流量方案。我们的两种算法变化过省电的特权性能,仍然提供约45%的可实现节省。

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