On efficient gossiping in radio networks

Leszek Ga̧sieniec

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

12 Scopus citations

Abstract

A communication network is very often modelled as a graph of connections in which the nodes exchange information (messages) via (un)directed links. An associated communication protocol determines the way the messages are exchanged. Among the most popular network models are: (1) the message passing model in which a node in one round can inform all its neighbours; (2) the telephone model also known as the matching model where in each round edges along which the exchange of messages is performed form a matching in the graph of connections. More recently, due to arrival of wireless technology (3) the radio network model attracted more attention in algorithms community. In this model, a message transmitted by a node is destined for all neighbours of this node. It is assumed, however, that due to interference a node can successfully receive a message if and only if exactly one of its neighbours transmits during this round. The two most fundamental problems in relation to information dissemination are: broadcasting (one-to-all communication) and gossiping (total information exchange). In broadcasting, the goal is to distribute a piece of information (broadcast message) from a distinguished source node to all other nodes in the network. In gossiping, however, each node in the network is expected to distribute its own message to every other node in the network. A lot of attention has been given to the broadcasting problem that resulted in a large volume of efficient algorithmic solutions in the models described above. However, much less is known about gossiping. The latter problem is more complex algorithmically (in principle it is a simultaneous multiple-source broadcasting) thus it concerns more advanced communication strategies. Further study on efficient gossiping methods gained recently an extra motivation through an increasing interest in, e.g., information aggregation methods that propel fundamental applications in sensor networks. Also when the use of randomisation is permitted gossiping provides an interesting context for a distributed version of the coupon collector problem. This paper is a short survey on the most important developments in efficient radio gossiping. We discuss deterministic as well as randomized methods of communication in the context of a variety of models taking into account knowledge in relation to the network size and topology, orientation of connections and the upper bound on the size of messages. Using this opportunity we also shed more light on several combinatorial structures and algorithmic solutions that emerged during studies on efficient radio broadcasting and gossiping.

Original languageEnglish (US)
Title of host publicationStructural Information and Communication Complexity - 16th International Colloquium, SIROCCO 2009, Revised Selected Papers
Pages2-14
Number of pages13
DOIs
StatePublished - Mar 22 2010
Externally publishedYes
Event16th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2009 - Piran, Slovenia
Duration: May 25 2009May 27 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5869 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2009
CountrySlovenia
CityPiran
Period5/25/095/27/09

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'On efficient gossiping in radio networks'. Together they form a unique fingerprint.

  • Cite this

    Ga̧sieniec, L. (2010). On efficient gossiping in radio networks. In Structural Information and Communication Complexity - 16th International Colloquium, SIROCCO 2009, Revised Selected Papers (pp. 2-14). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5869 LNCS). https://doi.org/10.1007/978-3-642-11476-2_2