CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
Reseach Article

Multi-Objective Node Placement Methodology for Wireless Sensor Network

Published on None 2010 by Rabindra ku Jena
Mobile Ad-hoc Networks
Foundation of Computer Science USA
MANETS - Number 2
None 2010
Authors: Rabindra ku Jena
36fd300d-48ba-45ad-b1d1-858046dec256

Rabindra ku Jena . Multi-Objective Node Placement Methodology for Wireless Sensor Network. Mobile Ad-hoc Networks. MANETS, 2 (None 2010), 84-88.

@article{
author = { Rabindra ku Jena },
title = { Multi-Objective Node Placement Methodology for Wireless Sensor Network },
journal = { Mobile Ad-hoc Networks },
issue_date = { None 2010 },
volume = { MANETS },
number = { 2 },
month = { None },
year = { 2010 },
issn = 0975-8887,
pages = { 84-88 },
numpages = 5,
url = { /specialissues/manets/number2/1017-58/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Mobile Ad-hoc Networks
%A Rabindra ku Jena
%T Multi-Objective Node Placement Methodology for Wireless Sensor Network
%J Mobile Ad-hoc Networks
%@ 0975-8887
%V MANETS
%N 2
%P 84-88
%D 2010
%I International Journal of Computer Applications
Abstract

Node placement is an important task in wireless sensor network. Node placement in wireless sensor network is a multi-objective combinatorial problem. A multi-objective evolutionary algorithm based framework has been proposed in this paper. Design parameters such as network density, connectivity and energy consumption have been taken into account for developing the framework. The framework optimizes the operational modes of the sensor nodes along with clustering schemes and transmission signal strengths.

References
  1. G. J. Pottie, “Wireless sensor networks,” Information Theory Workshop 1998, 139-140.
  2. M. Kodialam, T. Nandagopal, “Characterizing the achievable rates in multihop wireless networks,” Mobicom 2003.
  3. T. Dam, K. Langendoen, “An adaptive energy-efficient MAC protocol for Wireless Sensor Networks,” Sensys, 2003
  4. J. Pan, T. Hou, L. Cai, Y. Shi, S. Shen, “Topology control for Wireless Sensor Networks,” Mobicom, 2003
  5. A. Srinivas, E. Modiano, “Minimum energy disjoint path routing in wireless ad-hoc networks,” Mobicom, 2003
  6. K. Sundaresan, V. Anantharaman, H. Hsieh, R. Sivakumar, “ATP: a reliable transport protocol for ad-hoc networks,” Mobihoc, 2003.
  7. W. Heinzelman, “Application-specific protocol architecture for wireless networks,” Ph.D. Thesis, MIT, 2000.
  8. J. Rabaey, J. Ammer, T. Karalar, S. Li, et al, “Pico-radios for wireless sensor networks: the next challenge in ultra-low power design,” Digest of Technical Papers. ISSCC. IEEE International. Volume 2. 2002 156-445
  9. H. Kim, T. Abdelzaher, W. Kwon, “Minimum-energy asynchronous dissemination to mobile sinks in Wireless Sensor Network,” Sensys 2003.
  10. R. Min, A. Chandrakasan, “Energy-efficient communication for ad-hoc wireless sensor networks,” Conference Record of the Thirty-Fifth Asilomar Conference on Signals, Systems and Computers. Volume 1. (2001) 139-143.
  11. S. Sen, S. Narasimhan, K. Deb, “Sensor network design of linear processes using genetic algorithms”, Comput. Chem. Eng. 22 (3) (1998), pp. 385–390.
  12. S.A. Aldosari, J.M.F. Moura, “Fusion in sensor networks with communication constraints”, in: Information Processing in Sensor Networks (IPSN’04), Berkeley, CA, April 2004.
  13. D. Turgut, S.K. Das, R. Elmasri, B. Turgut, “Optimizing clustering algorithm in mobile ad hoc networks using genetic algorithmic approach”, in: IEEE GLOBECOM’02, Taipei,Taiwan, November 2002.
  14. G. Heyen, M.-N. Dumont, B. Kalitventzeff, “Computer-aided design of redundant sensor networks”, in: Escape 12, The Aague, The Netherlands, May 2002.
  15. S. Jin, M. Zhou, A.S. Wu, “Sensor network optimization using a genetic algorithm”, in: 7th World Multiconference on Systemics, Cybernetics and Informatics, Orlando, FL, 2003.
  16. D.B. Jourdan, O.L. de Weck, “Layout optimization for a wireless sensor network using a multi-objective genetic algorithm”, in: IEEE Semiannual Vehicular Technology Conference, Milan, Italy, May 2004.
  17. Konstantinos P. Ferentinos, Theodore A. Tsiligiridis, “Adaptive design optimization of wireless sensor networks using genetic algorithms”, Computer Networks 51 (2007),pp. 1031–1051
  18. O. Younis, S. Fahmy, “Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach”, in: INFOCOM 2004, Hong Kong,March, 2004.
  19. M. Younis, M. Youssef, K. Arisha, “Energy-aware routing in cluster based sensor networks”, in: 10th IEEE/ACM International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS 2002), Fort Worth, TX, October 2002.
  20. S. Bandyopadhyay, E.J. Coyle, “An energy efficient hierarchical clustering algorithm for wireless sensor networks”, in: IEEE INFOCOM 2003, San Francisco, CA, April 2003.
  21. D. Goldberg. Genetic algorithms in Sarch, Optimization,and Machine Learnig. Addision-Wesley Plublishing Company, New York, England, Bonn, Tokyo, 1989.
  22. C. A. Coello, G. Toscano, and M . Salazar. Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8(3):256–279, June 2004.
  23. Deb, K. Multi-Objective Optimization using Evolutionary Algorithms, John Wiley and Sons Ltd, pp. 245-253, 2002.
  24. T. B¨ack, G. R¨udolph, and H.P. Schwefel. A survey of evolution strategies. In Proceedings of the 4th International Conference on Genetic Algorithms, pages 2–9, 1991.
  25. T. B¨ack and H.P. Schwefel. Evolutionary algorithms:Some very old strategies for optimization and adaptation new computing techniques in physics research ii.In Proc. Second Int’lWorkshop Software Engineering, Artificial Intelligence, and Expert Systems for High Energy and Nuclear Physics, pages 247–254, 1992.
Index Terms

Computer Science
Information Sciences

Keywords

Network Configuration Sensor Placement Wireless Sensor Networks