ABSTRACT
Deterministic energy-efficient clustering protocol (DEC) is a dynamic, distributive, and self-organized method to reduce the energy consumption in the network. The DEC protocol promises a better and fixed number of Cluster Heads (CH) selections based on the remaining energy in its every round. DEC has various demerits like non-consideration of intra-cluster distance, disregard of the degree of the node. To address these issues of DEC, this chapter proposes Genetic Algorithm (GA)-based Deterministic Energy-Efficient Clustering Protocol, DEC-GA. In this work, K-means clustering is used for initial clustering on the homogeneous network and hybrid DEC-GA is used for CH selection. MATLAB-based recreation output shows that DEC-GA outwits on conventional DEC and improves the lifetime of the network. The performance matrices are evaluated and the calculated results indicate a significant improvement over the conventional protocols.
