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Simulation of Extended Clustering K-means (ECK) Technique for Multi- Tier Hierarchical WSN

Wireless sensor networks are self-adaptive and infrastructure free in nature. During their course of execution, they suffer several anomalies. One of such aberration is non uniform distribution of energy. This unequal energy distribution becomes catastrophic for large area heterogenous networks. This paper presents a decentralized approach for energy management; based on K-means algorithm before cluster formation in classic low energy adaptive hierarchical protocol. In this work, network is partitioned into many tiers. This has reduced effective Euclidian distance between a sender node and sink by improving centroid node selection. This work has increased network lifetime, reduced latencies in end-to-end data communication and also provided network stability by reducing size of clusters.