Dynamic data compression in multi-hop wireless networks

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Dynamic data compression in multi-hop wireless networks

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Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems table of contents

Seattle, WA, USA

SESSION: Power management table of contents

Pages 145-156

Year of Publication: 2009

ISBN:978-1-60558-511-6

Authors

Abhishek B. Sharma	University of Southern California, Los Angeles, CA, USA
Leana Golubchik	University of Southern California, Los Angeles, CA, USA
Ramesh Govindan	University of Southern California, Los Angeles, CA, USA
Michael J. Neely	University of Southern California, Los Angeles, CA, USA

Sponsors

ACM: Association for Computing Machinery
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation

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ACM New York, NY, USA

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ABSTRACT

Data compression can save energy and increase network capacity in wireless sensor networks. However, the decision of whether and when to compress data can depend upon platform hardware, topology, wireless channel conditions, and application data rates. Using Lyapunov optimization theory, we design an algorithm called SEEC that makes joint compression and transmission decisions with the goal of minimizing energy consumption. A practical distributed variant, DSEEC, is able to achieve more than 30% energy savings and adapts seamlessly across a wide range of conditions, without explicitly taking topology, application data rates, and link quality changes into account.

REFERENCES

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