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Distributed Compressive Sensing Based Data Gathering in Energy Harvesting Sensor Network

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Algorithms and Architectures for Parallel Processing (ICA3PP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9528))

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Abstract

Wireless sensor networks are gaining popularity in practical monitoring and surveillance applications. One of the major challenges for designing sensor networks is to minimize the transmission cost. Distributed compressive sensing is a promising technique for energy efficient data gathering in wireless sensor networks. In this paper, we propose a distributed compressive sensing-based data gathering scheme in energy harvesting sensor networks, in which the sensor readings possess both inter-(spatial) and intra-(temporal) signal correlations to improve the recovery quality of sensory data and prolong the sensor network’s lifetime as well. Besides, we also consider that the sensors operate with intermittently available energy that is harvested from the environment. A cluster-based routing strategy is exploited and a joint sparsity model is used for compressing the sensory data. Then the Simultaneous Orthogonal Matching Pursuit (SOMP) algorithm is designed to recover the sparse data. The simulation results show significant gain in terms of signal reconstruction accuracy and energy consumption.

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Acknowledgments

The authors would like to acknowledge that this work was partially supported by the National Natural Science Foundation of China (Grant No. 61379111, 61202342, 61402538, and 61403424) and Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20110162110042).

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, Changsha, 410075, Hunan, China

    Weirong Liu, Gaorong Qin, Fu Jiang, Kaiyang Liu & Zhengfa Zhu

Authors
  1. Weirong Liu
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  2. Gaorong Qin
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  3. Fu Jiang
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  4. Kaiyang Liu
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  5. Zhengfa Zhu
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Corresponding author

Correspondence to Fu Jiang .

Editor information

Editors and Affiliations

  1. Central South University, Changsha, China

    Guojun Wang

  2. The University of Sydney, Sydney, New South Wales, Australia

    Albert Zomaya

  3. University of Murcia, Murcia, Murcia, Spain

    Gregorio Martinez

  4. Hunan University , Changsha, China

    Kenli Li

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Liu, W., Qin, G., Jiang, F., Liu, K., Zhu, Z. (2015). Distributed Compressive Sensing Based Data Gathering in Energy Harvesting Sensor Network. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9528. Springer, Cham. https://doi.org/10.1007/978-3-319-27119-4_46

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  • DOI: https://doi.org/10.1007/978-3-319-27119-4_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27118-7

  • Online ISBN: 978-3-319-27119-4

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