Compressed Sensing-Based Data Gathering in WSN

Abstract:

This paper proposes an improved CS algorithm for WSN environmental monitoring. First, the algorithm applys approximate joint sparsity model (JSM) to analyze data. Further, with the improved clustering routing data gathering, that is, within each cluster applying CS-based data gathering methods, and cluster headers using the shortest path routing to sink node. Extensive simulation results show that this approach not only shrinks the distribution range of data processing to reduce recovery error, but greatly lessens numbers of data transmission times to maintain energy balance of the entire network.

• Periodical: Applied Mechanics and Materials (Volumes 519-520)
• Pages: 1258-1263
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.519-520.1258
• Online since: February 2014
• Authors: San Lin Jiang, Duo Long Wu, Yan Jie Wu
• Keywords: Compressed Sensing, Data Transmission, Recovery Error, Wireless Sensor Network (WSN)

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