Energy-distance & degree: multi-objective based optimized clustering and route discovery in wireless sensor network

Abstract

Network lifetime (NL) and energy preserving of sensor node is the most vital problem in the deployment of wireless sensor networks (WSNs ). An approach of cluster based path establishment shows the way in which cluster heads (CHs ) collect the information with each other and transfers into the sink (nS ) via multi-hop routing. In this paper, we present path establishment and CHs selection through Energy-Distance and Degree (EDD) based clustering (EDDCH) and route discovery (EDDRD). The networks divided into multiple groups and each CHs support to each other for data forwarding also the smaller sized clusters closest to the nS and huge size clusters remote from the S increases the lifetime of the network. The simulation results compared with the existing route optimization named as Particle Swarm Optimization (PSO) in terms of residual energy (RE ) and network lifetime (NL ).

Energy‐efficient model using optimal route discovery based on adaptive spider monkey optimization model

“…Followed by the computation of an appropriate distance, the transmitter power level is adjusted by the node. The mathematical expression in obtaining the receptive distance among the nodes is defined as follows 32 From Equation (), the receptive distance, overall distance, and the average receptive distance are represented .…”