Data compression trade-offs in sensor networks

Mo Chen; Mark L. Fowler

doi:10.1117/12.562187

18 October 2004 Data compression trade-offs in sensor networks

Mo Chen, Mark L. Fowler

Proceedings Volume 5561, Mathematics of Data/Image Coding, Compression, and Encryption VII, with Applications; (2004) https://doi.org/10.1117/12.562187
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

This paper first discusses the need for data compression within sensor networks and argues that data compression is a fundamental tool for achieving trade-offs in sensor networks among three important sensor network parameters: energy-efficiency, accuracy, and latency. Next, it discusses how to use Fisher information to design data compression algorithms that address the trade-offs inherent in accomplishing multiple estimation tasks within sensor networks. Results for specific examples demonstrate that such trades can be made using optimization frameworks for the data compression algorithms.

Citation Download Citation

Mo Chen and Mark L. Fowler "Data compression trade-offs in sensor networks", Proc. SPIE 5561, Mathematics of Data/Image Coding, Compression, and Encryption VII, with Applications, (18 October 2004); https://doi.org/10.1117/12.562187

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