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Reseach Article

Cluster based Energy Efficient Sensing for Cognitive Radio Sensor Networks

by Usman Mansoor, Muhammad Khalil Shahid
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 88 - Number 7
Year of Publication: 2014
Authors: Usman Mansoor, Muhammad Khalil Shahid
10.5120/15363-3849

Usman Mansoor, Muhammad Khalil Shahid . Cluster based Energy Efficient Sensing for Cognitive Radio Sensor Networks. International Journal of Computer Applications. 88, 7 ( February 2014), 14-19. DOI=10.5120/15363-3849

@article{ 10.5120/15363-3849,
author = { Usman Mansoor, Muhammad Khalil Shahid },
title = { Cluster based Energy Efficient Sensing for Cognitive Radio Sensor Networks },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 88 },
number = { 7 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 14-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume88/number7/15363-3849/ },
doi = { 10.5120/15363-3849 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:06:59.732106+05:30
%A Usman Mansoor
%A Muhammad Khalil Shahid
%T Cluster based Energy Efficient Sensing for Cognitive Radio Sensor Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 88
%N 7
%P 14-19
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a wireless cognitive radio sensor network is considered, where each sensor node is equipped with cognitive radio. As energy consumption is the main problem when using sensors therefore a new clustering algorithm is developed according to which group of nodes form cluster having a single cluster head. Each cluster has balanced energy which prolongs overall lifetime of CRSN. Cluster heads are rotated, depending on a threshold value, in such a way as to improve the lifetime of a cluster. As new cluster head is selected immediately whenever energy of old cluster head drops to certain threshold thus improves sensing results by CRSN nodes with minimum number of faulty decisions. Simulation results demonstrate working of schemes proposed and compares the pros and cons of each scheme.

References
  1. Ozgur B. Akan, Osman B. Karli, Ozgur Ergul, Cognitive Radio Sensor Networks. IEEE Network: The Magazine of Global Internetworking – Special issue title on networking over multi-hop cognitive networks, 2009, volume 23, pp. 34-40.
  2. Abolarinwa J. A, SalawuN and Achonu A, Cognitive Radio-based Wireless Sensor Networks As Next Generation Sensor Network: Concept, Problems and Prospects, Journal of Emerging Trends in Computing and Information Sciences, ISSN 2079-8407, Vol. 4, No. 8 August 2013.
  3. Tata Jagannadha Swamy, Thaskani Sandhya and Dr. Garimella Ramamurthy, Energy Efficient Architecture to Cognitive Radio Wireless Sensor Networks, International Journal of Computer Networks and Wireless Communications (IJCNWC), ISSN: 2250-3501, Vol. 2, No. 6, December 2012.
  4. Ameer Ahmed Abbasi and Mohamed Younis, A survey on clustering algorithms for wireless sensor networks, Computer Communications, 2007, volume 30, pp. 2826–2841.
  5. Ossama Younis and Sonia Fahmy, Distributed Clustering for Scalable, Long-Lived Sensor Networks, Extended abstract in the 9th Annual International Conference on Mobile Computing and Networking, 2003, ACM MobiCom, San Diego, CA.
  6. Renke Sun, Enjie Ding and Duan Zhao, The study of a wireless multimedia sensor network Self-Organization protocol for coal mine, 2nd International Conference on Computer Engineering and Technology, 2010, volume 4, Chengdu.
  7. Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks, in Proceedings of the 33rd Hawaii International Conference on System Sciences, 2000, volume 8, pp. 3005-3014.
Index Terms

Computer Science
Information Sciences

Keywords

Balanced energy clustering algorithm cluster head and cluster head rotation.