• DocumentCode
    108140
  • Title

    Transmission-Efficient Clustering Method for Wireless Sensor Networks Using Compressive Sensing

  • Author

    Ruitao Xie ; Xiaohua Jia

  • Author_Institution
    Dept. of Comput. Sci., City Univ. of Hong Kong, Kowloon, China
  • Volume
    25
  • Issue
    3
  • fYear
    2014
  • fDate
    Mar-14
  • Firstpage
    806
  • Lastpage
    815
  • Abstract
    Compressive sensing (CS) can reduce the number of data transmissions and balance the traffic load throughout networks. However, the total number of transmissions for data collection by using pure CS is still large. The hybrid method of using CS was proposed to reduce the number of transmissions in sensor networks. However, the previous works use the CS method on routing trees. In this paper, we propose a clustering method that uses hybrid CS for sensor networks. The sensor nodes are organized into clusters. Within a cluster, nodes transmit data to cluster head (CH) without using CS. CHs use CS to transmit data to sink. We first propose an analytical model that studies the relationship between the size of clusters and number of transmissions in the hybrid CS method, aiming at finding the optimal size of clusters that can lead to minimum number of transmissions. Then, we propose a centralized clustering algorithm based on the results obtained from the analytical model. Finally, we present a distributed implementation of the clustering method. Extensive simulations confirm that our method can reduce the number of transmissions significantly.
  • Keywords
    compressed sensing; data communication; telecommunication network routing; telecommunication traffic; wireless sensor networks; centralized clustering; compressive sensing; data collection; data transmissions; hybrid CS method; routing trees; traffic load; transmission-efficient clustering; wireless sensor networks; Clustering algorithms; Clustering methods; Compressed sensing; Data collection; Data communication; Routing; Vectors; Wireless sensor networks; clustering; compressive sensing; data collection;
  • fLanguage
    English
  • Journal_Title
    Parallel and Distributed Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9219
  • Type

    jour

  • DOI
    10.1109/TPDS.2013.90
  • Filename
    6487499