An energy based cluster head selection unequal clustering algorithm with dual sink (ECH-DUAL) for continuous monitoring applications in wireless sensor networks

The essential sections of the hot spot problem are network lifetime improvements and uniform residual energy distribution in wireless sensor networks (WSN). Clustering of sensor nodes is a significant process that improves network lifetime and energy efficiency of WSN. Usage of equal cluster sizes in WSN causes more energy to be consumed by the cluster heads when the data is routed to sink thus resulting in hot spot problems. Hence, recent research papers focus on unequal clustering where cluster size increases as the distance to the sink increases. In this paper, cluster heads are selected by modifying energy efficient unequal clustering mechanism (EEUC). This process is done in two ways. Firstly, in EEUC, final cluster heads are selected based on the residual energy of the randomly selected tentative cluster heads. In our algorithm, tentative cluster head is selected based on energy based timer, residual energy, node IDs and trust value. Final cluster head selection approach selects final CHs based on competition range, node degree and head count. Secondly, in applications like continuous monitoring, usage of static sink causes the clusters near the sink to die out faster, as the cluster heads in these clusters form the fixed path for data routing, hence resulting in hot spot problems. In this work, an energy based cluster head selection unequal clustering algorithm (ECH-DUAL) using dual (static and mobile) sink is proposed. The simulation shows that proposed system (ECH-DUAL) improves network lifetime of continuous monitoring wireless sensor networks significantly over EEUC.