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Investigating Optimization Techniques for Cluster Head Election in WSN
| Communications on Applied Electronics |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 5 - Number 2 |
| Year of Publication: 2016 |
| Authors: Amanjot Kaur, Gaurav Mehta |
10.5120/cae2016652226
|
Amanjot Kaur, Gaurav Mehta . Investigating Optimization Techniques for Cluster Head Election in WSN. Communications on Applied Electronics. 5, 2 ( May 2016), 28-37. DOI=10.5120/cae2016652226
Abstract
Wireless sensor network (WSN) is a briskly augmenting high-tech platform with remarkable and neoteric applications. Many new protocols specifically designed for the requirement of energy awareness are provided as per consequence of newfangled advances in WSN. In Actu, optimization of the network operation is vital to prolong network’s lifetime. For energy-efficiency in WSNs, one of the most accepted solutions is to cluster the networks. The regular nodes sensing the field and sending their data to the cluster-head, and then, transmitting to the base station is a process usually followed in a typical clustered WSN. Furthermore, cluster formation done inaptly, can make some CHs burdened with high number of sensor nodes. This overwork may lead to abrupt death of the CHs thereby deteriorating the overall performance of the WSN. Network Lifetime can be increased by preventing faster death of the highly loaded CHs. Three evolutionary algorithms namely Flower Pollination Algorithm (FPA), Harmony Search Algorithm (HSA) and Particle Swarm Optimization (PSO) with appropriate fitness functions are compared with the intrinsic properties of clustering in mind. The main idea is the embodiment of criteria of compactness (i.e. cohesion) and separation error in the fitness function to direct the search into promising solutions. The property of heterogeneity of nodes, in terms of their energy; in hierarchically clustered wireless sensor networks has also been involved. Simulation over 20 random heterogeneous WSNs shows that our FPA always prolongs the network lifetime, sustain more energy in comparison to the results obtained using the PSO and HSA protocols.
References
- W.Heinzelman, A.Chandrakasan, H.Balakrishnan, Energy-efficient communication protocol for wireless microsensor networks, in Proceedings of the 33rd International Conference on System Science(ICSS’00),Hawaii, U.S.A. ,pp 1-10, 2000
- M.A.Adnan, M.A.Razzaque, I.Ahmed and I.F.Isnin, Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey, Sensors 2014,Vol 14, pp.299-345,2014
- PratyayKuila, Prasanta K. Jana, A novel differential evolution based clustering algorithm for wireless sensor networks, Applied Soft Computing 25 (2014) 414–425
- Gupta, S.K., Kuila, P., Jana, P.K, GAR: an energy efficient GA-based routing for wireless sensor networks, In: ICDCIT 2013, LNCS 7753, 267–277, 2013.
- Saleem, M., et al.. Swarm intelligence based routing protocol for wireless sensor networks: survey and future directions. Inf. Sci, 181, 4597-4624, 2011.
- Kulkarni,R.V., Particle swarm optimization in wireless-sensor networks: a brief survey. IEEE Trans. Syst., Man, Cybern.–Part C: Appl. Rev.41, 262-267,2011
- Zungeru, A.M., Classical and swarm intelligence based routing protocols for wireless sensor networks: a survey and comparison. J. Netw. Comput. Appl, 35, 1508–1536, 2012.
- Kuila, P., Gupta, S.K., Jana, P.K, A novel evolutionary approach for load balanced clustering problem for wireless sensor networks”, Swarm Evol. Comput. 12, 48–56,2013
- Xin-She Yanga, Mehmet Karamanoglua, Xingshi He, Multi-objective Flower Algorithm for Optimization, International Conference on Computational Science, ICCS 2013, Procedia Computer Science 18 ( 2013 ) 861 – 868
- P. Kuila, 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.
- D.C. Hoang,P. Yadav,R. Kumar, and S.K. Panda, Real Time Implementation of a Harmony Search Algorithm based Clustering Protocol for Energy Efficient Wireless Sensor Networks, IEEE transactions on industrial informatics, Vol 10, pp. 774-783,2014.
- A. Immanuel Selvakumar and K. Thanushkodi , A new particle swarm optimization Solution to nonconvex economic dispatch problems, IEEE Trans. on power systems, Vol. 22, No. 1, pp. 42-51,2007.
- Z. W. Geem, J. H. Kim, and G. V. Loganathan, A new heuristic optimization algorithm: harmony search, Simulation, vol. 76, no. 2, pp. 60-68, 2001.
- G. Smaragdakis, I. Matta, A. Bestavros, SEP: a stable election protocol for clustered heterogeneous wireless sensor networks, in: Second International Workshop on Sensor and Actor Network Protocols and Applications (SANPA 2004), Boston, MA, 2004.
- Bara’a A. Attea, Enan A. Khalil, A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks, Applied Soft Computing 12 (2012) 1950–1957
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