Geographic gossip: Efficient averaging for sensor networks

Alexandros D.G. Dimakis, Anand D. Sarwate, Martin J. Wainwright

Research output: Contribution to journalArticlepeer-review

147 Scopus citations

Abstract

Gossip algorithms for distributed computation are attractive due to their simplicity, distributed nature, and robustness in noisy and uncertain environments. However, using standard gossip algorithms can lead to a significant waste of energy by repeatedly recirculating redundant information. For realistic sensor network model topologies like grids and random geometric graphs, the inefficiency of gossip schemes is related to the slow mixing times of random walks on the communication graph. We propose and analyze an alternative gossiping scheme that exploits geographic information. By utilizing geographic routing combined with a simple resampling method, we demonstrate substantial gains over previously proposed gossip protocols. For regular graphs such as the ring or grid, our algorithm improves standard gossip by factors of n and √n, respectively. For the more challenging case of random geometric graphs, our algorithm computes the true average to accuracy ε using O((n1.5/√log n) log ε-1) radio transmissions, which yields a √n/log n factor improvement over standard gossip algorithms. We illustrate these theoretical results with experimental comparisons between our algorithm and standard methods as applied to various classes of random fields.

Original languageEnglish (US)
Pages (from-to)1205-1216
Number of pages12
JournalIEEE Transactions on Signal Processing
Volume56
Issue number3
DOIs
StatePublished - Mar 2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Aggregation problems
  • Consensus problems
  • Distributed signal processing
  • Gossip algorithms
  • Message-passing algorithms
  • Random geometric graphs
  • Sensor networks

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