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NSDI '08 Abstract

Pp. 323336 of the Proceedings

Reducing Network Energy Consumption via Sleeping and Rate-Adaptation

Sergiu Nedevschi and Lucian Popa, University of California, Berkeley, and Intel Research, Berkeley; Gianluca Iannaccone and Sylvia Ratnasamy, Intel Research, Berkeley; David Wetherall, University of Washington and Intel Research, Seattle


We present the design and evaluation of two forms of power management schemes that reduce the energy consumption of networks. The first is based on putting network components to sleep during idle times, reducing energy consumed in the absence of packets. The second is based on adapting the rate of network operation to the offered workload, reducing the energy consumed when actively processing packets.

For real-world traffic workloads and topologies and using power constants drawn from existing network equipment, we show that even simple schemes for sleeping or rate-adaptation can offer substantial savings. For instance, our practical algorithms stand to halve energy consumption for lightly utilized networks (10-20%). We show that these savings approach the maximum achievable by any algorithms using the same power management primitives. Moreover this energy can be saved without noticeably increasing loss and with a small and controlled increase in latency ( < 10ms). Finally, we show that both sleeping and rate adaptation are valuable depending (primarily) on the power profile of network equipment and the utilization of the network itself.

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Last changed: 11 Aug 2008 mn