NSDI '08 – Abstract
Pp. 323–336 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
Abstract
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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