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Reseach Article

Comparative Study of Optimized Wireless Sensor Network Routing Protocols

by Ahmed O. Eid, Ibrahim E. Ziedan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 7
Year of Publication: 2018
Authors: Ahmed O. Eid, Ibrahim E. Ziedan
10.5120/ijca2018917576

Ahmed O. Eid, Ibrahim E. Ziedan . Comparative Study of Optimized Wireless Sensor Network Routing Protocols. International Journal of Computer Applications. 181, 7 ( Aug 2018), 10-17. DOI=10.5120/ijca2018917576

@article{ 10.5120/ijca2018917576,
author = { Ahmed O. Eid, Ibrahim E. Ziedan },
title = { Comparative Study of Optimized Wireless Sensor Network Routing Protocols },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2018 },
volume = { 181 },
number = { 7 },
month = { Aug },
year = { 2018 },
issn = { 0975-8887 },
pages = { 10-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number7/29783-2018917576/ },
doi = { 10.5120/ijca2018917576 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:05:17.429035+05:30
%A Ahmed O. Eid
%A Ibrahim E. Ziedan
%T Comparative Study of Optimized Wireless Sensor Network Routing Protocols
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 7
%P 10-17
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nowadays, Wireless sensor network applications are very important in most industrial fields. Most strategies are used to save energy of WSNs to prolong their life time. This problem attracted attention of many researches and many methods were proposed to optimize the energy consumption of WSNs. This paper presents a comparative study between two meta-heuristics algorithms are used to optimize this problem. One of them is the improved harmony search algorithm, and the other is the particle swarm optimization algorithm. Showing the strategies which are used to build its routing protocol and overviews on optimization algorithm which depend on build its solutions. Energy model used to calculate fitness of each solution. Improved algorithms are used in routing to solve the proposed problem. And propose termination criteria, simulation and results for each algorithm. At last this of them preferred to implement.

References
  1. T. He, S. Krishnamurthy, L. Luo, T. Yan, L. Gu, R. Stoleru, G. Zhou, Q. Cao, P. Vicaire, and J. A. Stankovic, “VigilNet: An integrated sensor network system for energy-efficient surveillance,” ACM Transactions on Sensor Networks (TOSN), vol. 2, no. 1, pp. 1-38, 2006.
  2. R. Szewczyk, A. Mainwaring, J. Polastre, J. Anderson, and D. Culler, "An analysis of a large scale habitat monitoring application." pp. 214-226.
  3. S. Kim, S. Pakzad, D. Culler, J. Demmel, G. Fenves, S. Glaser, and M. Turon, "Wireless sensor networks for structural health monitoring." pp. 427-428.
  4. P. Baronti, P. Pillai, V. W. Chook, S. Chessa, A. Gotta, and Y. F. Hu, “Wireless sensor networks: A survey on the state of the art and the 802.15. 4 and ZigBee standards,” Computer communications, vol. 30, no. 7, pp. 1655-1695, 2007.
  5. A. Thakkar, and K. Kotecha, “A new Bollinger Band based energy efficient routing for clustered wireless sensor network,” Applied Soft Computing, vol. 32, pp. 144-153, 2015.
  6. Y. Zhu, and L. M. Ni, "Probabilistic approach to provisioning guaranteed qos for distributed event detection." pp. 592-600.
  7. J. Hao, B. Zhang, and H. T. Mouftah, “Routing protocols for duty cycled wireless sensor networks: A survey,” IEEE Communications Magazine, vol. 50, no. 12, 2012.
  8. G. Anastasi, M. Conti, M. Di Francesco, and A. Passarella, “Energy conservation in wireless sensor networks: A survey,” Ad hoc networks, vol. 7, no. 3, pp. 537-568, 2009.
  9. R. Beraldi, R. Baldoni, and R. Prakash, “A biased random walk routing protocol for wireless sensor networks: The lukewarm potato protocol,” IEEE Transactions on Mobile Computing, vol. 9, no. 11, pp. 1649-1661, 2010.
  10. K. P. Naveen, and A. Kumar, "Tunable locally-optimal geographical forwarding in wireless sensor networks with sleep-wake cycling nodes." pp. 1-9.
  11. B. Zeng, and Y. Dong, “An improved harmony search based energy-efficient routing algorithm for wireless sensor networks,” Applied Soft Computing, vol. 41, pp. 135-147, 2016.
  12. C. Sivakumar, and P. L. Parthiban, “Energy Efficient Traffic Protocol in Wireless Sensor Networks Using Improved Metaheuristic Algorithm.”
  13. P. Kuila, and P. K. Jana, “Energy efficient clustering and routing algorithms for wireless sensor networks: Particle swarm optimization approach,” Engineering Applications of Artificial Intelligence, vol. 33, pp. 127-140, 2014.
  14. M. Hasnat, M. Akbar, Z. Iqbal, Z. Khan, U. Qasim, and N. Javaid, "Bio inspired distributed energy efficient clustering for Wireless Sensor Networks." pp. 1-7.
  15. D. Lobiyal, C. Katti, and A. Giri, “Parameter value optimization of ad-hoc on demand multipath distance vector routing using particle swarm optimization,” Procedia Computer Science, vol. 46, pp. 151-158, 2015.
  16. D. Sahin, V. C. Gungor, T. Kocak, and G. Tuna, “Quality-of-service differentiation in single-path and multi-path routing for wireless sensor network-based smart grid applications,” Ad Hoc Networks, vol. 22, pp. 43-60, 2014.
  17. I. F. Akyildiz, and M. C. Vuran, Wireless sensor networks: John Wiley & Sons, 2010.
  18. W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, “An application-specific protocol architecture for wireless microsensor networks,” IEEE Transactions on wireless communications, vol. 1, no. 4, pp. 660-670, 2002.
  19. D. Bratton, and J. Kennedy, "Defining a standard for particle swarm optimization." pp. 120-127.
  20. P. Kuila, S. K. Gupta, and P. K. Jana, “A novel evolutionary approach for load balanced clustering problem for wireless sensor networks,” Swarm and Evolutionary Computation, vol. 12, pp. 48-56, 2013.
  21. C. P. Low, C. Fang, J. M. Ng, and Y. H. Ang, “Efficient load-balanced clustering algorithms for wireless sensor networks,” Computer Communications, vol. 31, no. 4, pp. 750-759, 2008.
  22. A. Bari, A. Jaekel, and S. Bandyopadhyay, “Clustering strategies for improving the lifetime of two-tiered sensor networks,” Computer Communications, vol. 31, no. 14, pp. 3451-3459, 2008.
  23. M. Cardei, and D.-Z. Du, “Improving wireless sensor network lifetime through power aware organization,” Wireless Networks, vol. 11, no. 3, pp. 333-340, 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Wireless Sensor Network Routing Protocols meta-heuristic Harmony Search particle swarm