Multi QoS constrained data sharing using hybridized pareto-glowworm swarm optimization

Abstract

Wireless sensor network (WSN) is the group of sensor nodes which attempts to monitor and share the data. Secured and reliable routing in the WSN is the most arduous task which needs to be performed with more concern for the stable output. In the existing work clustering based symbiotic organism search method is used to share the data with assured reliability and packet delivery ratio. However, this approach lacks performance due to the intruder, and it is resolved in the proposed method by introducing the novel method namely hybridized pareto-glowworm swarm optimization and authenticated data communication. In this paper, cluster head selection is made by considering multiple quality of service parameters such mobility and energy whereas in the previous research only energy is considered. To select the optimal cluster head with multiple objectives, a pareto optimal method is hybridized with the GSO algorithm for the multi-objective fitness evaluation. Here formation of clusters is purely based on the selected cluster Head. After clustering, data is gathered from the multiple sensor nodes which are aggregated to reduce the bandwidth utilization and forwarded to the base station. To ensure the security level in this work authentication between the cluster head and the base station is done and then data is transmitted. The experimental results concluded that the proposed method has a better result than the existing methods.