Cluster based architecture for Cognitive Radio Network

Manoj Ramachandran, Harish Sheeranalli Venkatarama, Sandesh Hebbar

Research output: Contribution to journalArticle

Abstract

Catastrophic events like flood often result in the derangement of the communication networks. The consequences include difficulty in locating the survivors of the disaster. The purpose of this paper is to give an insight to the design and development of a Cognitive Radio Network that can be used as an immediate remedy communication network which can help in such situations. The architecture based on clustering in adhoc mode is explored in order to develop an algorithm for implementing the cluster based cognitive network that focuses on yielding longer cluster lifetime. This implementation creates a cluster with less backbone network that improves the efficiency in routing and multicasting. By using the network simulation tools, performance analysis of this clustering architecture is done and the stability of the clustering based on the parameters and the relationship between the nodes and clusters is noted.

Original languageEnglish
Pages (from-to)10-26
Number of pages17
JournalJournal of Computer Science
Volume15
Issue number1
DOIs
Publication statusPublished - 01-01-2019

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Cognitive radio
Telecommunication networks
Multicasting
Disasters

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Ramachandran, Manoj ; Venkatarama, Harish Sheeranalli ; Hebbar, Sandesh. / Cluster based architecture for Cognitive Radio Network. In: Journal of Computer Science. 2019 ; Vol. 15, No. 1. pp. 10-26.
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Ramachandran, M, Venkatarama, HS & Hebbar, S 2019, 'Cluster based architecture for Cognitive Radio Network' Journal of Computer Science, vol. 15, no. 1, pp. 10-26. https://doi.org/10.3844/jcssp.2019.10.26

Cluster based architecture for Cognitive Radio Network. / Ramachandran, Manoj; Venkatarama, Harish Sheeranalli; Hebbar, Sandesh.

In: Journal of Computer Science, Vol. 15, No. 1, 01.01.2019, p. 10-26.

Research output: Contribution to journalArticle

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