SURF: A distributed channel selection strategy for data dissemination in multi-hop cognitive radio networks

Mubashir Husain Rehmani, Aline Carneiro Viana, Hicham Khalife, Serge Fdida

Research output: Contribution to journalArticlepeer-review

90 Citations (Scopus)

Abstract

In this paper, we propose an intelligent and distributed channel selection strategy for efficient data dissemination in multi-hop cognitive radio network. Our strategy, SURF, classifies the available channels and uses them efficiently to increase data dissemination reliability in multi-hop cognitive radio networks. The classification is done on the basis of primary radio unoccupancy and of the number of cognitive radio neighbors using the channels. Through extensive NS-2 simulations, we study the performance of SURF compared to four related approaches. Simulation results confirm that our approach is effective in selecting the best channels for efficient communication (in terms of less primary radio interference) and for highest dissemination reachability in multi-hop cognitive radio networks.

Original languageEnglish
Pages (from-to)1172-1185
Number of pages14
JournalComputer Communications
Volume36
Issue number10-11
DOIs
Publication statusPublished - Jun 2013
Externally publishedYes

Keywords

  • Channel selection
  • Data dissemination
  • Multi-hop cognitive radio networks

Fingerprint

Dive into the research topics of 'SURF: A distributed channel selection strategy for data dissemination in multi-hop cognitive radio networks'. Together they form a unique fingerprint.

Cite this