Abstract
Grouping of sensor nodes in clusters has several advantages including energy efficiency, network scalability, and efficient data aggregation. Many clustering protocols have been developed till date promising better energy efficiency in comparison with others. In this paper, we have surveyed important clustering techniques with a focus on the estimation of optimum number of clusters. We have also presented a case study on LEACH protocol, suggesting that under certain conditions clustering is not a wise solution, a non-clustered network or a network with mixed approach can give better result. Experimental results show significant improvement in lifetime and throughput.
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Notes
- 1.
Time from network initialization till first node dies.
References
Benzerbadj A, Kechar B, Bounceur A, Hammoudeh M (2018) Surveillance of sensitive fenced areas using duty-cycled wireless sensor networks with asymmetrical links. J Netw Comput Appl 112:41–52
Chan TJ, Chen CM, Huang YF, Lin JY, Chen TR (2008) Optimal cluster number selection in ad-hoc wireless sensor networks. WSEAS Trans Commun 7(8):837–846
Chen H, Megerian S (2006) Cluster sizing and head selection for efficient data aggregation and routing in sensor networks. In: Wireless communications and networking conference, 2006. WCNC 2006, vol 4. IEEE, pp 2318–2323
Fang K, Liu C, Teng J (2018) Cluster-based optimal wireless sensor deployment for structural health monitoring. Struct Health Monitor 17(2):266–278
Halgamuge MN, Zukerman M, Ramamohanarao K, Vu HL (2009) An estimation of sensor energy consumption. Prog Electromagn Res B
Heinzelman W, Chandrakasan A, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wireless Commun 1(4):660–670. https://doi.org/10.1109/TWC.2002.804190
Kumar V, Yadav S, Kumar V, Sengupta J, Tripathi R, Tiwari S (2018) Optimal clustering in Weibull distributed WSNs based on realistic energy dissipation model. In: Progress in computing, analytics and networking. Springer, pp 61–73
Lu W, Gong Y, Liu X, Wu J, Peng H (2018) Collaborative energy and information transfer in green wireless sensor networks for smart cities. IEEE Trans Ind Inform 14(4):1585–1593
Miranda K, Zapotecas-MartĂnez S, LĂłpez-Jaimes A, GarcĂa-Nájera A (2019) A comparison of bio-inspired approaches for the cluster-head selection problem in WSN. In: Advances in nature-inspired computing and applications. Springer, pp 165–187
Pattem S, Krishnamachari B, Govindan R (2008) The impact of spatial correlation on routing with compression in wireless sensor networks. ACM Trans Sensor Netw (TOSN) 4(4):24
Rice J, Mechitov K, Sim SH, Spencer B Jr, Agha G (2011) Enabling framework for structural health monitoring using smart sensors. Struct Control Health Monitor 18(5):574–587
Ross SRJ, Friedman NR, Dudley KL, Yoshimura M, Yoshida T, Economo EP (2018) Listening to ecosystems: data-rich acoustic monitoring through landscape-scale sensor networks. Ecol Res 33(1):135–147
Roy NR, Chandra P (2018) A note on optimum cluster estimation in leach protocol. IEEE Access 6:65690–65696
Selvakennedy S, Sinnappan S, Shang Y (2007) A biologically-inspired clustering protocol for wireless sensor networks. Comput Commun 30(14–15):2786–2801
Smaragdakis G, Matta I, Bestavros A (2004) SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. Tech. rep., Boston University Computer Science Department
Tiwari T, Roy NR (2015) Hierarchical clustering in heterogeneous wireless sensor networks: a survey. In: 2015 international conference on computing, communication & automation (ICCCA). IEEE, pp 1385–1390
Vlajic N, Xia D (2006) Wireless sensor networks: to cluster or not to cluster? In: Proceedings of the 2006 international symposium on a world of wireless, mobile and multimedia networks. IEEE Computer Society, pp 258–268
Zanjireh MM, Larijani H (2015) A survey on centralised and distributed clustering routing algorithms for WSNs. In: 2015 IEEE 81st vehicular technology conference (VTC Spring). IEEE, pp 1–6
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Roy, N.R., Chandra, P. (2020). Estimation of Optimum Number of Clusters in WSN. In: Khanna, A., Gupta, D., Bhattacharyya, S., Snasel, V., Platos, J., Hassanien, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1059. Springer, Singapore. https://doi.org/10.1007/978-981-15-0324-5_47
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DOI: https://doi.org/10.1007/978-981-15-0324-5_47
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