Energy Efficient Hybrid Clustering Algorithm for Wireless Sensor Network

Improvements to sensor devices including micro-electro mechanical devices that are used for information collection and dissemination has led to the introduction of Wireless Sensor Networks (WSN). Sensor nodes in a WSN are deployed over an area to collect data from the surroundings and to perform additional actions including data aggregation and storage, computations and data transmission to gateway devices. Clustering is a technique used to organize and structure the sensor network to split it into sub-networks, each with a controller node called the Cluster Head (CH). This technique reduces sensor node energy consumption and prolongs the network lifetime. The CH aggregates the data from the respective cluster members and transmits the aggregated data to the next level in the network. In this paper, a clustering algorithm named Energy Aware Neighbor Oriented Clustering (EANOC) is proposed to improve the network lifetime. EANOC is underpinned by earlier work into a Hybrid Weight Based Clustering Algorithm (HWCA) and focuses on a new neighborhood discovery type. The selection of the propagation model, transmission range, and the receiver signal strength indication value have a significant impact on the rate of energy utilization. Simulation results show that EANOC outperforms HWCA and the Dynamic Load-Balancing Cluster-Based Protocol in attaining longer network lifetime.