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Reseach Article

Particle Swarm Optimization Based Methodology for Node Placement in Wireless Sensor Networks

Published on None 2011 by Cavill D’Souza, Shreyans Mulkutkar, Kinn Savla, Sanjay Gandhe
journal_cover_thumbnail
International Conference and Workshop on Emerging Trends in Technology
Foundation of Computer Science USA
ICWET - Number 14
None 2011
Authors: Cavill D’Souza, Shreyans Mulkutkar, Kinn Savla, Sanjay Gandhe
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Cavill D’Souza, Shreyans Mulkutkar, Kinn Savla, Sanjay Gandhe . Particle Swarm Optimization Based Methodology for Node Placement in Wireless Sensor Networks. International Conference and Workshop on Emerging Trends in Technology. ICWET, 14 (None 2011), 8-14.

@article{
author = { Cavill D’Souza, Shreyans Mulkutkar, Kinn Savla, Sanjay Gandhe },
title = { Particle Swarm Optimization Based Methodology for Node Placement in Wireless Sensor Networks },
journal = { International Conference and Workshop on Emerging Trends in Technology },
issue_date = { None 2011 },
volume = { ICWET },
number = { 14 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 8-14 },
numpages = 7,
url = { /proceedings/icwet/number14/2172-is469/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology
%A Cavill D’Souza
%A Shreyans Mulkutkar
%A Kinn Savla
%A Sanjay Gandhe
%T Particle Swarm Optimization Based Methodology for Node Placement in Wireless Sensor Networks
%J International Conference and Workshop on Emerging Trends in Technology
%@ 0975-8887
%V ICWET
%N 14
%P 8-14
%D 2011
%I International Journal of Computer Applications
Abstract

In this paper a Particle Swarm Optimization (PSO) based technique for generating a heterogeneous network configuration comprising assignment of shouters and whisperers to available node positions is proposed. The generated network configuration is optimized to obtain desired network characteristics. The proposed technique is compared with contemporary evolutionary techniques such as Genetic Algorithms (GA) for performance.

References
  1. I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, “Wireless sensor networks: a survey”, Computer Networks 38(2002), pp. 393–422.
  2. Zhou, B. Krishnamachari, “Localized topology generation mechanisms for wireless sensor networks”, in: IEEE GLOBECOM’ 03, San Francisco, CA, December 2003.
  3. S. Ghiasi, A. Srivastava, X. Yang, M. Sarrafzadeh, “Optimal energy aware clustering in sensor networks”, Sensors 2 (2002), pp. 258–269.
  4. Bhondekar, R. Vig, M. L. Singla, C Ghanshyam, P. Kapur, “Genetic algorithm based node placement methodology for wireless sensor networks”, IMECS 2009, Hong Kong, 2009..
  5. H. Chen, D. Qian, W. Wu, L. Cheng, “Swarm Intelligence based energy balance routing for wireless sensor networks”, Second international symposium on intelligent information technology application, 2008.
  6. S. Bandyopadhyay, E.J. Coyle, “An energy efficient hierarchical clustering algorithm for wireless sensor networks”, in: IEEE INFOCOM 2003, San Francisco, CA, April 2003.
  7. G. Ferrari, “Sensor Networks”, Springer Publications, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Particle Swarm Optimization (PSO) Wireless Sensor Networks (WSN)