An energy-efficient adaptive clustering algorithm with load balancing for wireless sensor network

Maximisation of network lifetime is the issue of prime importance in Wireless Sensor Network (WSN). An energy–efficient clustering algorithm with load balancing can achieve this challenging goal. We propose Density–based Dynamic Clustering (DDC) algorithm for clustering and cluster head election mechanism with the use of independence set. Furthermore, a distributed algorithm (DISD - Distributed Independence Set Discovery) is designed for cluster head election in O(1) complexity per sensor node. In this, we dynamically find an optimal sensor cover to dominate maximum sensors within a cluster, therefore forming an InDependence Set (IDS). Only the members of IDS are allowed to participate in the cluster head selection (rotation), thereby establishing load balancing and energy management. Our model is designed for dual modes: low– and high–traffic session. According to the flow of packets, the sleep management technique is modified. Network simulator is used for the simulation of our proposed algorithms.