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Improving Data Dissemination in Multi-Hop Cognitive Radio Ad-Hoc Networks

Mubashir Husain Rehmani 1 Aline Carneiro Viana 2 Hicham Khalife 3 Serge Fdida 1 
1 NPA - Networks and Performance Analysis
LIP6 - Laboratoire d'Informatique de Paris 6
2 ASAP - As Scalable As Possible: foundations of large scale dynamic distributed systems
UR1 - Université de Rennes 1, Inria Saclay - Ile de France, INSA - Institut National des Sciences Appliquées, CNRS - Centre National de la Recherche Scientifique : UMR
Abstract : In this paper, we present SURF, a distributed channel selection strategy for efficient data dissemination in multi-hop cognitive radio ad-hoc networks (CRNs). SURF classifies the available channels on the basis of primary radio unoccupancy and the number of cognitive radio neighbors using the channels. Through extensive NS-2 simulations, we compare the performance of SURF with three related approaches. Simulation results confirm that SURF is effective in selecting the best channels for efficient communication and for highest dissemination reachability in multi-hop CRNs.
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Submitted on : Friday, October 7, 2011 - 4:41:52 PM
Last modification on : Saturday, June 25, 2022 - 10:32:40 AM
Long-term archiving on: : Tuesday, November 13, 2012 - 3:30:45 PM


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Mubashir Husain Rehmani, Aline Carneiro Viana, Hicham Khalife, Serge Fdida. Improving Data Dissemination in Multi-Hop Cognitive Radio Ad-Hoc Networks. ADHOCNETS 2011 - 3rd International ICST Conference on Ad Hoc Networks, ICST, Sep 2011, Paris, France. pp.117-130, ⟨10.1007/978-3-642-29096-1_9⟩. ⟨inria-00630225⟩



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