Article

Somniloquy: augmenting network interfaces to reduce PC energy usage

Authors:

Yuvraj Agarwal,

Ranveer Chandra,

Rajesh GuptaAuthors Info & Claims

NSDI'09: Proceedings of the 6th USENIX symposium on Networked systems design and implementation

Pages 365 - 380

Published: 22 April 2009 Publication History

Abstract

Reducing the energy consumption of PCs is becoming increasingly important with rising energy costs and environmental concerns. Sleep states such as S3 (suspend to RAM) save energy, but are often not appropriate because ongoing networking tasks, such as accepting remote desktop logins or performing background file transfers, must be supported. In this paper we present Somniloquy, an architecture that augments network interfaces to allow PCs in S3 to be responsive to network traffic. We show that many applications, such as remote desktop and VoIP, can be supported without application-specific code in the augmented network interface by using application-level wakeup triggers. A further class of applications, such as instant messaging and peer-to-peer file sharing, can be supported with modest processing and memory resources in the network interface. Experiments using our prototype Somniloquy implementation, a USB-based network interface, demonstrates energy savings of 60% to 80% in most commonly occuring scenarios. This translates to significant cost savings for PC users.

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Information

Published In

cover image Guide Proceedings

NSDI'09: Proceedings of the 6th USENIX symposium on Networked systems design and implementation

April 2009

480 pages

Program Chairs:
Jennifer Rexford
Princeton University
,
Emin Gün Sirer
Cornell University

Sponsors

USENIX Assoc: USENIX Assoc

Publisher

USENIX Association

United States

Publication History

Published: 22 April 2009

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Guo LZhai SQiao YLin FDan TDahlia M(2019)TranskernelProceedings of the 2019 USENIX Conference on Usenix Annual Technical Conference10.5555/3358807.3358865(675-691)Online publication date: 10-Jul-2019
https://dl.acm.org/doi/10.5555/3358807.3358865
Zhao HHua QChen HYe YWang HTan STlelo-Cuautle E(2018)Thermal-Sensor-Based Occupancy Detection for Smart Buildings Using Machine-Learning MethodsACM Transactions on Design Automation of Electronic Systems10.1145/320090423:4(1-21)Online publication date: 28-Jun-2018
https://dl.acm.org/doi/10.1145/3200904
Dabaghi FMovahedi ZLangar R(2017)A survey on green routing protocols using sleep-scheduling in wired networksJournal of Network and Computer Applications10.1016/j.jnca.2016.10.00577:C(106-122)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1016/j.jnca.2016.10.005
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