ENL Publications

Abstract

Abhishek B. Sharma, Leana Golubchik, Ramesh Govindan, Michael J. Neely, Dynamic Data Compression in Multi-hop Wireless Networks, In Proceedings of the ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems, June 2009. [PDF] [BIB]

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.

@inproceedings{Sharma09,
	author = {Abhishek B. Sharma and Leana Golubchik and Ramesh Govindan and Michael J. Neely},
	title = {{Dynamic Data Compression in Multi-hop Wireless Networks}},
	booktitle = "Proceedings of the ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems",
	year = "2009",
	month = "June",
	address = "",
}