EEC-GA: Energy-Efficient Clustering Approach Using Genetic Algorithm for Heterogeneous Wireless Sensor Networks

In a wireless sensor network (WSN), sensor nodes are distributed in a predefined environment, collecting environmental data and transferring them to the base station or sink for processing and analysis. In the meantime, much research has been done on heterogeneous wireless sensor networks. Due to the fact that in a heterogeneous wireless sensor network (HWSN) factors such as primary energy, data processing ability, etc. greatly affect the life of the network, the selection of cluster heads (CHs) for coordinating a cluster of sensor nodes has created a wide range for further development of network efficiency capabilities. In this work, an event-driven energy-efficient protocol based on a genetic algorithm is proposed that uses various parameters such as the remaining energy of the node, the minimum distance of a node to the base station, and also the degree of the neighborhood of a node as fitness function values, and evaluates solutions in a heterogeneous wireless sensor network. For evaluating the proposal, network stability, energy consumption, death of the first node, and number of living nodes per round are considered as evaluation criteria.