The nodes lifetime maximization is one of the serious problems in the wireless sensor networks (WSNs). Clustering technique demonstrate to the most popular solution for enhancing sum of expended energy of WSNs. Every sensor can oversee an occasion and send data to its cluster head (CH) which totals and transmits data to the BS (BS) through different CHs in the network in clustered WSNs. This situation induces the hot spot` issue where closer CHs to the BS will die prior due to the overwhelming transfer data. Unequal clustering techniques have attempted to tackle this issue and control the extent of each cluster in the network. In this paper, we proposed another unequal clustering calculation called energy degree distance unequal clustering algorithm (EDDUCA) planning with maintenance to adjust energy utilization and expand the lifetime of the network. EDDUCA utilizes the `Sierpinski triangle` technique so as to divide network into unequal clusters. The derived outcomes show that EDDUCA-M can adequately adjust the energy utilization and thusly can extend the lifetime of network.

Unequal clustering, WSN, Energy efficiency, Lifetime, Cluster maintenance

[1] Arjunan, S. and Pothula, S., “A survey on unequal clustering protocols in Wireless Sensor Networks”, Journal of King Saud University-Computer and Information Science, 2017.
[2] Kumar, D., Aseri, T. C., & Patel, R. B,”EEHC: energy efficient heterogeneous clustered scheme for wireless sensor networks”, Computer Communications, Vol.32, pp. 662–667, 2009.
[3] Xiang, M., Shi, W. R., Jiang, C. J., & Zhang, Y,” Energy efficient clustering algorithm for maximizing lifetime of wireless sensor networks” ,International Journal of Electronics and Communications, Vol.64, pp.289–298, 2010.
[4] Bagci, H., &Yazici, “An energy aware fuzzy approach to unequal clustering in wireless sensor networks”, Applied Soft Computing, Vol.13, pp. 1741–1749, 2013.
[5] Jiguo, Y., Yingying, G., &Guanghui, W. “An energy-driven unequal clustering protocol for heterogenous wireless sensor networks” ,Journal of Control Theory and Applications, Vol.9, Issue.1, pp.133–139, 2011.
[6] Ye, M., Li, C., Chen, GH., & Wu, J.,” EECS: An energy efficient clustering scheme in wireless sensor networks”, In 24th IEEE international performance, computing, and communication conference, pp. 535–540, 2005.
[7] Jun, Y., Weiming, Z., Weidong, X., Daquan, T., &Jiuyang, T. ,”Energy efficient and balanced cluster-based data aggregation algorithm for wireless sensor networks”, Procedia Engineering, Vol. 29, pp.2009–2015, 2012.
[8] Li, C., Ye, M., Chen, G., & Wu, J. “An energy-efficient unequal clustering mechanism for Wireless sensor network”, In IEEE international conference on mobile adhoc and sensor systems conference, pp. 596–640, 2005.
[9] Song, M., Chenglin, Z., Zheng, Z., &Yabin, Y, ”An improved fuzzy unequal clustering algorithm for wireless sensor network” ,Mobile Network Application Journal, LLC, pp.206–214, 2012.
[10] Arjunan, S. and Sujatha, P., “Lifetime maximization of wireless sensor network using fuzzy based unequal clustering and ACO based routing hybrid protocol”.,Applied Intelligence, pp.1-18, 2018.
[11] Uthayakumar J, Vengattaraman T, Dhavachelvan P. ,”A new lossless neighborhood indexing sequence (NIS) algorithm for data compression in wireless sensor networks”, Ad Hoc Networks,. pp.149-57,2009.