A high connectivity cluster routing for energy-balanced wireless sensor network

Collection of information from critical situations where human beings find difficult to exist is a challenging task. In such scenarios tiny micro-sensors are densely deployed for monitoring the target objects or observing certain events to occur. The sensor nodes collect information from the target nodes, communicate with their neighbors and then forward the information to the base station for further action. However, the sensor nodes have limited battery power, minimal processing capability, and short transmission range. Existence of the network for a longer period can support for information gathering. In this paper we propose the high-connectivity cluster routing (HCCR) a novel static cluster-based dynamic cluster head routing algorithm for efficient energy management in sensor network. HCCR uses localized coordination to support scalability and incorporates data fusion into the routing to avoid redundant information that must be transmitted to the base station located nearby the network. We divide the whole network into different clusters. A cluster head (CH) is selected from a cluster considering maximum residual energy and Euclidean distance to all other nodes present in the cluster. We have conducted simulation-based evaluations to compare the performance of HCCR against enhanced energy-efficient protocol with static clustering (E³PSC) [8]. Our simulation results show that HCCR outperforms E³PSC in terms of network lifetime and power consumption.