Estimation localization in wireless sensor network based on multi-objective grey wolf optimizer

Abstract

Determining the position of nodes of a network plays an important role in many wireless sensor networks (WSN) applications e.g. in tracking, detecting, monitoring, etc. In this paper, the multiobjective grey wolf optimizer (MGWO) for the estimating approaches of the located nodes in a network is proposed to solve the multi-objective optimization localization issues in WSNs. There two objective functions related to the estimation localization are the distance of nodes and the geometric topology that consider to formula multiobjective optimization localization. The simulation results show considerable improvements in terms of localization accuracy and convergence rate in comparison with those obtained from the other methods.