Abstract
Energy efficient routing protocol is the requirement of today’s wireless sensor networks. Various protocols have been developed in order to create an energy efficient wireless sensor network, but still some loopholes exist in this domain and energy hole is one of them. Energy hole refers to the early energy diminution of those nodes that are near to the sink. This study introduced a mobile sink based energy aware clustering mechanism to enhance the lifetime of the network by overcoming the issue of energy holes. In proposed work, the network is initially divided into the number of rectangular regions and each region is comprised of one cluster head (CH). The nature-inspired firefly optimization algorithm is used to select cluster heads where residual energy, average node to node distance and distance from the node to sink are the decisive parameters of the process. The sink moves in the observing field after estimating the centroid location of the CHs. The performance of the proposed work is compared with the LEACH, LEACH-GA, A-LEACH, MIEEPB, and MSIEEP by using Matlab simulation platform. The result section represents the proficiency of the proposed MSECA protocol over traditional techniques in term of network lifetime, packet delivery ratio and packet delay.
Similar content being viewed by others
References
Abo-Zahhad M, Ahmed SM, Sabor N, Sasaki S (2015) Mobile sink based adaptive immune energy-efficient clustering protocol for improving the lifetime and stability period of wireless sensor networks. IEEE Sens J 15(8):4576–4586
Al-Karaki JN, Kamal AE (2004) Routing techniques in wireless sensor networks: a survey. IEEE Wirel Commun 11(6):6–28
Anand V, Agrawal D, Tirkey P, Pandey S (2016) An energy Efficient approach to extend network lifetime of wireless sensor networks. Procedia Comput Sci 92:425–430
Cerulli R, Donato RD, Raiconi A (2012) Exact and heuristic methods to maximize network lifetime in wireless sensor networks with adjustable sensing ranges. Eur J Oper 220(1):58–66
Chen G, Li C, Ye M, Wu J (2009) An unequal cluster-based routing protocol in wireless sensor networks. Wirel Netw 15(2):193–207
Curry R, Smith JC (2016) A survey of optimization algorithms for wireless sensor network lifetime maximization. Comput Ind Eng 101:145–166
Fister I, Fister I Jr, Yang XS, Brest J (2013) A comprehensive view of firefly algorithms. Swarm Evol Comput 13:34–46
Gupta V, Pandey R (2016) An improved energy aware distributed unequal clustering protocol for wireless sensor networks. Eng Sci Technol Int J 19:1050–1058
Hamida E, Chelius G (2008) Strategies for data dissemination to mobile sinks in wireless sensor networks. IEEE Wirel Commun 15:31–37
Han Z, Wu J, Zhang J, Liu L, Tian K (2014) A general self -organized tree-based energy-balance routing protocol for wireless sensor network. IEEE Trans Nucl Sci 61(2):732–740
Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 1(4):660–670
Jafri MR, Javaid N, Javaid A, Khan ZA (2013) Maximizing the lifetime of multi-chain PEGASIS using sink mobility. World Appl Sci J 21(9):1283–1289
Jayram BG, Ashoka DV (2016) Validation of multiple mobile elements based data gathering protocols for dynamic and static scenarios in wireless sensor networks. Procedia Comput Sci 92:260–266
Juhi R, Srivastava T, Sudarshan SB (2015) A genetic fuzzy system based optimized zone based energy efficient routing protocol for mobile sensor networks (OZEEP). Appl Soft Comput 37:863–886
Kim J, In J, Hur K, Kim JW, Eom DS (2010) An intelligent agent based routing structure for mobile sinks in WSNs. IEEE T Consum Electr 6(4):2310–2316
Kumar V, Kumar A (2018) Improving reporting delay and lifetime of a WSN using controlled mobile sinks. A J Intell Human Comput 10(4):1433–1441
Lindsey S, Raghavendra C, Sivalingam KM (2002) Data Gathering algorithms in sensor networks using energy metrics. IEEE Trans Parallel Distrib Syst 13:924–935
Liu JL, Ravishankar CV (2011) LEACH-GA: genetic algorithm-based energy-efficient adaptive clustering protocol for WSNs. Int J Mach Learn Comput 1(1):79–85
Mantri DS, Prasad NR, Prasad R (2016) Node heterogeneity for energy efficient synchronization in wireless sensor network. Procedia Comput Sci 79:885–892
Mottaghi S, Zahabi MR (2015) Optimizing LEACH clustering algorithm with mobile sink and rendezvous nodes. Int J Electron Commun 69:507–514
Pantazis NA, Nikolidakis SA, Vergados DD (2013) Energy efficient routing protocols in wireless sensor networks: a survey. IEEE Commun Surv Tutor. 15(2):551–590
Pesovic UM, Mohorko JJ, Benkic K, Cucej ZF (2010) single- hop vs. multi-hop energy efficiency analysis in wireless sensor networks. In: Proceedings of 18th Telecommunications Forum TELFOR, Belgrade, Serbia, pp 471–474
Salim MM, Elsayed HA, Ramly SE (2014) PR-LEACH approach for balancing energy dissipation of LEACH protocol for WSNs. In: Proceedings of 31st national radio science conference, Ain Shams University, Egypt, pp 252–259
Shankar T, Shanmugavel S, Rajesh A (2016) Hybrid HSA and PSO algorithm for energy efficient cluster head selection in wireless sensor networks. Swarm Evol Comput 30:1–10
Siavoshi S, Kavian YS, Sharif H (2016) Load- balanced energy efficient clustering protocol for wireless sensor networks. IET Wirel Sens Syst 6(3):67–73
Touati Y, Chérif AA, Daachi B (2017) Optimization techniques for energy consumption in WSNs. In: Touati Y, Chérif AA, Daachi B (eds) Energy management in wireless sensor networks. ISTE, Elsevier, pp 9–22
Verma A, Prasad JS (2017) Performance enhancement by efficient ant colony routing algorithm based on swarm intelligence in wireless sensor networks. Int J Wirel Mob Comput 12(3):131–138
Vijayvargiya KG, Shrivastava V (2012) An amend implementation on LEACH protocol based on energy hierarchy. Int J Curr Eng Technol 2(4):427–431
Yang XS, He X (2013) Firefly algorithm: recent advances and applications. Int J Swarm Intell 1(1):36–50
Yang Y, Lai C, Lin W (2013) An energy efficient clustering algorithm for wireless sensor networks In: Proceedings of 10th IEEE international conference on control and automation (ICCA) Hangzhou, China, 12–14 June, pp 1382–1385
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Chauhan, V., Soni, S. Mobile sink-based energy efficient cluster head selection strategy for wireless sensor networks. J Ambient Intell Human Comput 11, 4453–4466 (2020). https://doi.org/10.1007/s12652-019-01509-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-019-01509-6