A High-Grained Traffic Prediction for Microseconds Power Control in Energy-Aware Routers

Sou Koyano, S. Ata, I. Oka, K. Inoue
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引用次数: 6

Abstract

Recently, as significant increase of Internet traffic, power consumption of ICT devices is growing dramatically. Energy-saving of routers is one of important problems in future networks. There are some studies to reduce the power consumption by adjusting routers' performance according to the volume of incoming/outgoing traffic. In such routers high-grained and accurate prediction of future traffic is very important for controlling power savings. In this paper, we propose a traffic prediction method suitable for performance adjustable routers which achieves accurate traffic prediction in short-term. We discuss about the impacts of prediction parameters and their tuning methods, for accurate of prediction. Through trace-driven simulations with real traffic, we show that our prediction method can reduce up to 95% of power consumption without any packet loss.
能量感知路由器中微秒功率控制的高粒度流量预测
近年来,随着互联网流量的显著增加,ICT设备的功耗也在急剧增长。路由器的节能是未来网络的重要问题之一。有一些研究通过根据进出流量的大小调整路由器的性能来降低功耗。在这种路由器中,对未来流量的高粒度和准确预测对于控制功耗节约非常重要。本文提出了一种适用于性能可调路由器的流量预测方法,可以在短期内实现准确的流量预测。讨论了预测参数的影响及其调整方法,以提高预测的准确性。通过真实流量的跟踪驱动仿真,我们表明我们的预测方法可以在没有丢包的情况下减少高达95%的功耗。
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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