Secure clustering-based energy efficient protocol using hybrid soft computing

Abstract

A hybrid protocol is proposed which utilizes secure clustering and hybrid soft computing to improve the network lifetime. Ant colony optimization (ACO) and Particle swam optimization (PSO) with crossover operator are used to design a hybrid soft computing-based inter-cluster data aggregation. Initially, cluster heads are selected based upon adaptive threshold function. Recommendation-based signatures are then assigned to every aggregated data. Then, tree-based data aggregation comes in action and collects sensing information directly from cluster heads by utilizing short distance obtained from the hybrid soft computing. The use of compressive sensing reduces the packet size which is going to be transmitted in the sensor network. Extensive analysis shows that the hybrid protocol considerably enhances network lifetime by conserving the energy in more efficient manner than other protocols at present deployed for sensor networks.