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Pervasive Computing: A Networking Perspective and Future Directions pp 93–102Cite as

Performance Evaluation of Unitary Measurement Matrix in Compressed Data Gathering for Real-Time Wireless Sensor Network Applications

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Abstract

Recently, compressed sensing has emerged as a novel phenomenon of simultaneous sampling and compressing any sparse signal. Wireless sensor network which is resource constrained requires to preserve its energy by various mechanisms. Each sensor node in wireless sensor network records the data in its surrounding which generates number of signals in the entire network. Communication process consumes maximum energy in the network as compared to other in network processes. So, energy may be preserved by reducing data rate in network by using distributed compressed sensing. In this paper, we propose to use a unitary matrix as measurement matrix to perform distributed compressed sensing to exploit both spatial and temporal correlation in sensor network data. The parameters used for measuring performance of the proposed scheme are the percentage by which overall network lifetime increases and the mean squared error in reconstruction of the original signal from compressed signal at the sink.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India

    Prateek Dolas & D. Ghosh

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  1. Prateek Dolas
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  2. D. Ghosh
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Correspondence to Prateek Dolas .

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Editors and Affiliations

  1. School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

    Deepshikha Bhargava

  2. Amity Institute of Information Technology, Amity University Rajasthan, Jaipur, Rajasthan, India

    Sonali Vyas

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Dolas, P., Ghosh, D. (2019). Performance Evaluation of Unitary Measurement Matrix in Compressed Data Gathering for Real-Time Wireless Sensor Network Applications. In: Bhargava, D., Vyas, S. (eds) Pervasive Computing: A Networking Perspective and Future Directions. Springer, Singapore. https://doi.org/10.1007/978-981-13-3462-7_9

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  • DOI: https://doi.org/10.1007/978-981-13-3462-7_9

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