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Efficient Selection Scheme for Data Processing in Wireless Sensor Networks

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Ahmed A.A. Gad-ElRab, Doaa M. Alhilaly
10.5120/ijca2016909230

Ahmed A A Gad-ElRab and Doaa M Alhilaly. Article: Efficient Selection Scheme for Data Processing in Wireless Sensor Networks. International Journal of Computer Applications 139(8):8-16, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Ahmed A.A. Gad-ElRab and Doaa M. Alhilaly},
	title = {Article: Efficient Selection Scheme for Data Processing in Wireless Sensor Networks},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {139},
	number = {8},
	pages = {8-16},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Recently, many data processing applications in wireless sensor networks (WSNs) works efficiently by using a coverage percentage of a target sensing area and a satisfaction percentage of collected data. Therefore, the whole coverage and complete satisfaction are not needed. As a result, finding new data processing techniques that can successfully minimize the data traffic and energy consumption for maximizing the network lifetime are required. In addition, using clustering with data processing techniques is an effective topology control approach in wireless sensor networks, which can increase network scalability and lifetime. In this paper, a ( -cov, -sat) data processing problem is introduced and a new mobile agent clustering data processing methods are proposed. The proposed methods use a clustering with a mobile agent to cover  percentage of the target area such that the satisfaction percentage of collected data is percentage. Simulation results show that the proposed methods achieve higher improvements in network lifetime, load balance and energy consumption than the existing methods.

References

  1. Wooldridge, Michael, and Nicholas R. Jennings. "Intelligent agents: Theory and practice." Knowledge engineering review 10.2 (1995): 115-152.‏
  2. J Fan H Huang S Zhang, Y Sun. Cooperative data processing algorithm based on mobile agent in wireless sensor networks. International Journal of Distributed Sensor Networks, Vol.2012, 2012.
  3. M. Chen, S. Gonzalez, and V. C. M. Leung, Applications and design issues for mobile agents in wireless sensor networks, IEEEm Wireless Communications, vol. 14, no. 6, pp. 20–26, 2007.
  4. Y. C. Tseng, S. P. Kuo, H. W. Lee, and C. F. Huang, Location tracking in a wireless sensor network by mobile agents and its data fusion strategies,Computer Journal, vol. 47, no. 4, pp. 448–460, 2004
  5. H. Qi and F. Wang, Optimal itinerary analysis for mobile agents in ad hoc wireless sensor networks, in Proceedings of the IEEE International Conference on Communications (ICC ’01), Helsinki, Finland, June 2001.
  6. Dilip Kumar and RB Patel. Multi-hop data communication algorithm for clustered wireless sensor networks. International Journal of Distributed Sensor Networks, Vol.2011, 2011.
  7. G. Sharma and R. Mazumdar, Hybrid sensor networks: a small world, in Proceedings of the 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MOBIHOC ’05), pp. 366–377, usa, May 2005.
  8. W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, An application-specific protocol architecture for wireless microsensor networks, IEEE Transactions on Wireles Communications, vol. 1, no. 4, pp. 660–670, 2002.
  9. G. Xin, W. H. Yang, and B. DeGang, EEHCA: an energy efficient hierarchical clustering algorithm for wireless sensor networks, Information Technology Journal, vol. 7, no. 2, pp. 245–252, 2008.
  10. O. Younis and S. Fahmy, HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks, IEEE Transactions on Mobile Computing, vol. 3, no. 4, pp. 366– 379, 2004.
  11. F. Xianging and S. Yulin, Improvement on LEACH protocol of wireless sensor networks, in Proceeding of International Conference on Sensor Technologies and Applications, pp. 260– 264, 2007.
  12. A. A. Abbasi and M. Younis, A survey on clustering algorithms forwireless sensor networks, Computer Communications, vol. 30, no. 14-15, pp. 28262841, 2007.
  13. G. Anastasi, M. Conti, M. D. Francesco, and A. Passarella, Energy conservation in wireless sensor networks: a survey, Ad Hoc Networks, vol. 7, no. 3, pp. 537568, 2009.
  14. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, A survey on sensor networks, IEEE Communications Magazine, vol. 40, no. 8, pp. 102105, 2002.
  15. H. Qi, Y. Xu, and X.Wang, Mobile-agent-based collaborative signal and information processing in sensor networks, Proceedings of the IEEE, vol. 91, no. 8, pp. 11721183, 2003.
  16. J. J. Chang, P. C. Hsiu, and T. W. Kuo, Search-oriented deployment strategies for wireless sensor networks, in Proceedings of the 10th IEEE International Symposium on Object and Component-Oriented Real- Time Distributed Computing (ISORC 07), pp. 164171, Santorini Island, Greece,May 2007.
  17. I. Joe, A path selection algorithm with energy efficiency for wireless sensor networks, in Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management, and Applications (SERA 07), pp. 419423, August 2007.
  18. M. Chen, K. Taekyoung, and C. Yanghee, Data dissemination based on mobile agent in wireless sensor networks, in Proceedings of the IEEE Conference on Local Computer Networks (LCN 05), pp. 527528, Sydney, Australia, November 2005.
  19. Karp, Richard M. Reducibility Among Combinatorial Problems. Complexity of Computer Computations, page 85-103. Plenum Press, New York, 1972.
  20. A. Varga and Andrs, The OMNeT++ Discrete Event Simulation System, in Proceedings of the European Simulation Multiconference (ESM’2001). Prague, Czech Republic, June 2001.
  21. Ahmed AA Gad-ElRab, Afaf AS Zaghrout, and Doaa M Alhilaly. Mobile agent cluster-based algorithm for data processing in wireless sensor networks. International Journal of Current Engineering and Technology, Vol.4(No.6):PP.65, Dec 2014.

Keywords

Mobile agent, cluster head , partial coverage, satisfaction