Abstract
One of the most promising algorithms for network optimization is the particle swarm optimization (PSO) and genetic algorithm (GA). The paper is about comparing these two as applied to wireless sensor networks. If a sink is placed at a longer distance from the sensors then the battery life (energy) drains faster, and it reduces the life of the network. Our analysis shows that optimized clustering technique of sensors can minimize the communication distance and can help to increase the network stability. GA and PSO can optimize the cluster formation of sensors. Simulation results have shown us that PSO performs better than GA for clustering algorithms in wireless sensor networks.
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References
Handy, M.J., Haase, M., Timmermann, D.: Low energy adaptive clustering hierarchy with deterministic cluster-head selection. In: 4th International Workshop on Mobile and Wireless Communications Network, 2002, pp. 368–372. IEEE (2002)
Qiao, X., Yan, C.: A control algorithm based on double cluster-head for heterogeneous wireless sensor network. In: 2nd International Conference on Industrial and Information Systems, vol. 1, pp. 541–544 (2010)
Singh, S.K., Singh, M.P., Singh, D.K.: A survey of energy efficient hierarchical cluster-based routing in wireless sensor networks. Int. J. Adv. Netw. Appl. 02(02), 570–580 (2010)
Kumar, N., Kaur, J.: Improved leach protocol for wireless sensor networks. In: 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), pp. 1–5. IEEE (2011)
Mehta, R., Pandey, A., Kapadia, P.: Reforming clusters using C-LEACH in wireless sensor networks. In: 2012 International Conference on Computer Communication and Informatics (ICCCI), pp. 1–4. IEEE (2012)
Xu, J., Jin, N., Lou, X., Peng, T., Zhou, Q., Chen, Y.: Improvement of LEACH protocol for WSN. In: 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 2174–2177. IEEE (2012)
Kaur, P., Katiyar, M.: The energy-efficient hierarchical routing protocols for WSN: a review. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 2(11), 194–199 (2012)
Rengugadevi, G., Sumithra, M.G.: Hierarchical routing protocols for wireless sensor network—a survey. Int. J. Smart Sens Ad Hoc Netw. (IJSSAN) 2(1), 71–75 (2012)
Norouzi, A., Zaim, A.H.: An integrative comparison of energy efficient routing protocols in wireless sensor network. Sci. Res. Wirel. Sensor Netw. 4, 65–67 (2012)
Gnanambigai, J., Rengarajan, D.N., Anbukkarasi, K.: Leach and its descendant protocols: a survey. Int. J. Commun. Comput. Technol. 1(3), 15–21 (2012)
Aslam, M., Javaid, N., Rahim, A., Nazir, U., Bibi, A., Khan, Z.A.: Survey of extended LEACH-based clustering routing protocols for wireless sensor networks. In: 2012 IEEE 14th International Conference on High Performance Computing and Communication and 2012 IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), pp. 1232–1238. IEEE (2012)
Neetika, S.K.: Review on hierarchical routing in wireless sensor networks. Int. J. Smart Sens. Ad Hoc Netw. (IJSSAN) 2(3), 85–90 (2012)
Kaur, R., Sharma, D., Kaur, N.: Comparative analysis of leach and its descendant protocols in wireless sensor network. Int. J. P2P Netw. Trends Technol. 3(1), 51–55 (2013)
Jan, M.A., Khan, M.: A survey of cluster-based hierarchical routing protocols. IRACST Int. J. Comput. Netw. Wirel. Commun. (IJCNWC) 3, 138–143 (2013)
Bhattacharjee, A., Bhallamudi, B., Maqbool, Z.: Energy-efficient hierarchical cluster based routing algorithm in WSN: a survey. Int. J. Eng. Res. Technol. (IJERT) 2(5), 302–311 (2013)
Verma, S., Mehta, R., Sharma, D., Sharma, K.: Wireless sensor network and hierarchical routing protocols: a review. Int. J. Comput. Trends Technol. (IJCTT) 4(8), 2411–2416 (2013)
Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: An application-specific protocol architecture for wireless microsensor networks. IEEE Trans. Wirel. Commun. 1(4), 660–670 (2002)
Gopakumar, A., Jacob, L.: Performance of some metaheuristic algorithms for localization in wireless sensor networks. Int. J. Netw. Manage. 19, 355–373 (2009)
Leung, S.Y.S., Tang, Y., Wong, W.K.: A hybrid particle swarm optimization and its application in neural networks. Expert Syst. Appl. 39, 395–405 (2012)
Chen, D.B., Zhao, C.X.: Particle swarm optimization with adaptive population size and its application. Appl. Soft Comput. 9(1), 39–48 (2009)
Tillett, J., Rao, R., Sahin, F.: Cluster-head identification in ad hoc sensor networks using particle swarm optimization. In: 2002 IEEE International Conference on Personal Wireless Communications, pp. 201–205. IEEE (2002)
Hussain, S., Matin, A.W., Islam, O.: Genetic algorithm for energy efficient clusters in wireless sensor networks. In: Fourth International Conference on Information Technology, 2007. ITNG’07, pp. 147–154. IEEE (2007)
Ostrosky, R., Rabani, Y.: Polynomial-time approximation schemes for geometric min-sum median clustering. J. ACM 49(2), 139–156 (2002)
Agarwal, P.K., Procopiuc, C.M.: Exact and approximation algorithms for clustering. Algorithmica 33(2), 201–226 (2002)
Jin, S., Zhou, M., Wu, A.S.: Sensor network optimization using a genetic algorithm. In: Proceedings of the 7th World Multiconference on Systemics, Cybernetics and Informatics, pp. 109–116 (2003)
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Parwekar, P., Rodda, S., Vani Mounika, S. (2018). Comparison between Genetic Algorithm and PSO for Wireless Sensor Networks. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Computing and Informatics . Smart Innovation, Systems and Technologies, vol 77. Springer, Singapore. https://doi.org/10.1007/978-981-10-5544-7_39
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DOI: https://doi.org/10.1007/978-981-10-5544-7_39
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