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Fast Decentralized Averaging via Multi-scale Gossip

  • Konstantinos I. Tsianos
  • Michael G. Rabbat
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6131)

Abstract

We are interested in the problem of computing the average consensus in a distributed fashion on random geometric graphs. We describe a new algorithm called Multi-scale Gossip which employs a hierarchical decomposition of the graph to partition the computation into tractable sub-problems. Using only pairwise messages of fixed size that travel at most \(O(n^{\frac{1}{3}})\) hops, our algorithm is robust and has communication cost of O(n loglogn logε − 1) transmissions, which is order-optimal up to the logarithmic factor in n. Simulated experiments verify the good expected performance on graphs of many thousands of nodes.

Keywords

Sensor Network Wireless Sensor Network Communication Cost Hierarchy Level Multiscale Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Konstantinos I. Tsianos
    • 1
  • Michael G. Rabbat
    • 1
  1. 1.Department of Electrical and Computer EngineeringMcGill UniversityMontrealCanada

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