Ring-Based Optimal-Level Distributed Wavelet Transform with Arbitrary Filter Length for Wireless Sensor Networks

  • Siwang Zhou1,

    Affiliated with

    • Yaping Lin1Email author and

      Affiliated with

      • Yonghe Liu2

        Affiliated with

        EURASIP Journal on Advances in Signal Processing20072008:396126

        DOI: 10.1155/2008/396126

        Received: 1 May 2007

        Accepted: 8 November 2007

        Published: 9 December 2007

        Abstract

        We propose an optimal-level distributed transform for wavelet-based spatiotemporal data compression in wireless sensor networks. Although distributed wavelet processing can efficiently decrease the amount of sensory data, it introduces additional communication overhead as the sensory data needs to be exchanged in order to calculate the wavelet coefficients. This tradeoff is explored in this paper with the optimal transforming level of wavelet transform. By employing a ring topology, our scheme is capable of supporting a broad scope of wavelets rather than specific ones, and the "border effect" generally encountered by wavelet-based schemes is also eliminated naturally. Furthermore, the scheme can simultaneously explore the spatial and temporal correlations among the sensory data. For data compression in wireless sensor networks, in addition to minimizing energy and consumption, it is also important to consider the delay and the quality of reconstructed sensory data, which is measured by the ratio of signal to noise ( http://static-content.springer.com/image/art%3A10.1155%2F2008%2F396126/MediaObjects/13634_2007_Article_2266_IEq1_HTML.gif ). We capture this with http://static-content.springer.com/image/art%3A10.1155%2F2008%2F396126/MediaObjects/13634_2007_Article_2266_IEq2_HTML.gif metric and using it to evaluate the performance of the proposed scheme. Theoretically and experimentally, we conclude that the proposed algorithm can effectively explore the spatial and temporal correlation in the sensory data and provide significant reduction in energy and delay cost while still preserving high http://static-content.springer.com/image/art%3A10.1155%2F2008%2F396126/MediaObjects/13634_2007_Article_2266_IEq1_HTML.gif compared to other schemes.

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        Authors’ Affiliations

        (1)
        School of Software, Hunan University
        (2)
        Department of Computer Science and Engineering, The University of Texas at Arlington

        Copyright

        © Siwang Zhou et al. 2008

        This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.