Sharing multiple messages over mobile networks

Yuxin Chen, Sanjay Shakkottai, Jeffrey G. Andrews

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Information dissemination in a large network is typically achieved when each user shares its own information or resources with each other user. Consider n users randomly located over a fixed region, and k of them wish to flood their individual messages among all other users, where each user only has knowledge of its own contents and state information. The goal is to disseminate all messages using a low-overhead strategy that is one-sided and distributed while achieving an order-optimal spreading rate over a random geometric graph. In this paper, we investigate the random-push gossip-based algorithm where message selection is based on the sender's own state in a random fashion. It is first shown that random-push is inefficient in static random geometric graphs. Specifically, it is Ω(n) times slower than optimal spreading. This gap can be closed if each user is mobile, and at each time moves locally using a random walk with velocity ν(n). We propose an efficient dissemination strategy that alternates between individual message flooding and random gossiping. We show that this scheme achieves the optimal spreading rate as long as the velocity satisfies ν(n) = ω(√log n/k). The key insight is that the mixing introduced by this velocity-limited mobility approximately uniformizes the locations of all copies of each message within the optimal spreading time, which emulates a balanced geometry-free evolution over a complete graph.

Original languageEnglish (US)
Title of host publication2011 Proceedings IEEE INFOCOM
Pages658-666
Number of pages9
DOIs
StatePublished - 2011
EventIEEE INFOCOM 2011 - Shanghai, China
Duration: Apr 10 2011Apr 15 2011

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X

Other

OtherIEEE INFOCOM 2011
Country/TerritoryChina
CityShanghai
Period4/10/114/15/11

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering

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