Abstract
In a large scale Wireless Sensor Networks (WSNs), designing an energy balanced clustering protocol has become a challenging research issues. This is due to fact that design of an energy-balanced clustering for maximizing the network lifetime of WSNs is a NP-hard problem. For solving this NP-hard problem, many meta-heuristic approach based clustering protocols are proposed in the recent years. However, these existing clustering protocols suffer from unbalanced energy consumption problem. In this problem, cluster heads are not uniformly distributed and overloaded cluster heads die out faster than under-loaded cluster heads. In order to solve this problem, we have proposed an energy balanced clustering protocol using particle swarm optimization called EBC-PSO. In the proposed protocol, we have used a novel multi-objective fitness function which contains three constraints such as average intra-cluster distance, residual energy and average cluster size. A detailed evaluation and performance comparison of the EBC-PSO with the three most popular protocols such as LEACH, PSO-ECHS, and E-OEERP are included.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Latiff, N.M.A., Tsimenidis, C.C., Sharif, B.S.: Energy-aware clustering for wireless sensor networks using particle swarm optimization. In: 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications. IEEE (2007)
Gupta, G.P.: Efficient coverage and connectivity aware data gathering protocol for wireless sensor networks. In: 3rd IEEE International Conference on Recent Advances in Information Technology (RAIT-2016), pp. 50–55 (2016)
Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Annual Hawaii International Conference on System Sciences. IEEE (2000)
Lindsey, S., Raghavendra, C.S.: PEGASIS: power-efficient gathering in sensor information systems. In: IEEE Aerospace Conference Proceedings, vol. 3. IEEE (2002)
Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mob. Comput. 3(4), 366–379 (2004)
Loscri, V., Morabito, G., Marano, S.: A two-levels hierarchy for low-energy adaptive clustering hierarchy (TL-LEACH). In: IEEE Vehicular Technology Conference, vol. 62. no. 3. IEEE (1999, 2005)
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)
Rao, P.C.S., Jana, P.K., Banka, H.: A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks. Wirel. Netw. 1–16
Rejina Parvin, J., Vasanthanayaki, C.: Particle swarm optimization-based clustering by preventing residual nodes in wireless sensor networks. IEEE Sens. J. 15(8), 4264–4274 (2015)
Kennedy, J.: Particle Swarm Optimization. Encyclopedia of Machine Learning, pp. 760–766. Springer, New York (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Jha, S., Gupta, G.P. (2018). Energy Balanced Clustering Protocol Using Particle Swarm Optimization for Wireless Sensor Networks. In: Satapathy, S., Joshi, A. (eds) Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 2. ICTIS 2017. Smart Innovation, Systems and Technologies, vol 84. Springer, Cham. https://doi.org/10.1007/978-3-319-63645-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-63645-0_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-63644-3
Online ISBN: 978-3-319-63645-0
eBook Packages: EngineeringEngineering (R0)