The impact of mobility on gossip algorithms

Anand Dilip Sarwate, Alexandros G. Dimakis

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


The influence of node mobility on the convergence time of averaging gossip algorithms in networks is studied. It is shown that a small number of fully mobile nodes can yield a significant decrease in convergence time. A method is developed for deriving lower bounds on the convergence time by merging nodes according to their mobility pattern. This method is used to show that if the agents have 1-D mobility in the same direction, the convergence time is improved by at most a constant. Upper bounds on the convergence time are obtained using techniques from the theory of Markov chains and show that simple models of mobility can dramatically accelerate gossip as long as the mobility paths overlap significantly. Simulations verify that different mobility patterns can have significantly different effects on the convergence of distributed algorithms.

Original languageEnglish (US)
Article number6157082
Pages (from-to)1731-1742
Number of pages12
JournalIEEE Transactions on Information Theory
Issue number3
StatePublished - Mar 2012
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


  • Consensus protocols
  • Markov chains
  • distributed algorithms
  • distributed averaging
  • distributed processing
  • gossip protocols
  • mobility
  • peer-to-peer networks
  • wireless sensor networks


Dive into the research topics of 'The impact of mobility on gossip algorithms'. Together they form a unique fingerprint.

Cite this