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Distributed Approximation and Tracking Using Selective Gossip

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Compressed Sensing & Sparse Filtering

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

This chapter presents selective gossip which is an algorithm that applies the idea of iterative information exchange to vectors of data. Instead of communicating the entire vector and wasting network resources, our method adaptively focuses communication on the most significant entries of the vector. We prove that nodes running selective gossip asymptotically reach consensus on these significant entries, and they simultaneously reach an agreement on the indices of entries which are insignificant. The results demonstrate that selective gossip provides significant communication savings in terms of the number of scalars transmitted. In the second part of the chapter we propose a distributed particle filter employing selective gossip. We show that distributed particle filters employing selective gossip provide comparable results to the centralized bootstrap particle filter while decreasing the communication overhead compared to using randomized gossip to distribute the filter computations.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, McGill University, Montreal, QC, Canada

    Deniz Üstebay, Mark Coates & Michael Rabbat

  2. Department of Mathematics, Eindhoven University of Technology, Eindhoven, The Netherlands

    Rui Castro

Authors
  1. Deniz Üstebay
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  2. Rui Castro
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  3. Mark Coates
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  4. Michael Rabbat
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Corresponding author

Correspondence to Deniz Üstebay .

Editor information

Editors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, Nanyang Technical University, Singapore, Singapore

    Avishy Y. Carmi

  2. School of Computing and Communications, Lancaster University, Lancaster, United Kingdom

    Lyudmila Mihaylova

  3. Department of Engineering, University of Cambridge, Cambridge, United Kingdom

    Simon J. Godsill

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Üstebay, D., Castro, R., Coates, M., Rabbat, M. (2014). Distributed Approximation and Tracking Using Selective Gossip. In: Carmi, A., Mihaylova, L., Godsill, S. (eds) Compressed Sensing & Sparse Filtering. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38398-4_10

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  • DOI: https://doi.org/10.1007/978-3-642-38398-4_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38397-7

  • Online ISBN: 978-3-642-38398-4

  • eBook Packages: EngineeringEngineering (R0)

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