Distributed semi‐adaptive compressive sensing data collection in wireless sensor networks |
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| Authors: | Saeed Mehrjoo Farshad Khunjush |
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| Affiliation: | 1. Department of Computer Science and Engineering, Dariun Branch, Islamic Azad University, Dariun, Iran;2. Department of Computer Science and Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran |
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| Abstract: | Recently, many researches have been conducted to exploit the compressive sensing (CS) theory in wireless sensor networks (WSNs). One of the most important goals in CS is to prolong the lifetime of WSNs. But CS may suffer from some errors during the reconstruction phase. In addition, an adaptive version of CS named Bayesian compressive sensing has been studied to improve the reconstruction accuracy in WSNs. This paper investigates these adaptive methods and identifies their associated problems. Finally, a distributed and semi‐adaptive CS‐based data collection method is proposed. The proposed method tackles the aforementioned problems. Simulation results show that considering both lifetime and accuracy factors as a compound metric, the proposed method yields a 200% improvement compared with the Bayesian compressive sensing‐based method and outperforms other compared methods in the literature. |
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| Keywords: | accuracy compressive sensing lifetime wireless sensor network |
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