Error Minimization in Localization of Wireless Sensor Networks Using Differential Evolution with Mobile Anchor Positioning (de - Map) Algorithm

Sensor Node Localization is considered to be one of the most critical issues in a Wireless Sensor Network (WSN). The objective of localization is determination of physical co-ordinates of a group of sensor nodes. The location information plays a vital role for coverage, deployment of sensor nodes and rescue operations. Many applications such as routing and target tracking are all location dependent. This work aims at determining the location of the sensor nodes with high precision. The initial part of this work is carried out by localizing the nodes using Mobile Anchor Positioning (MAP), a range-free localization method. As the anchors move through the network, they broadcast their location as beacon packets. The sensor nodes use the location information of beacon packets obtained from mobile anchors as well as the location packets from neighbouring nodes to calculate their location. Our proposed algorithm used for Localization is Differential Evolution with Mobile Anchor Positioning (DE MAP). We have incorporated DE – MAP algorithm over the results of MAP to enhance the location accuracy. The idea is to compare the performance of DE-MAP algorithm to Genetic Algorithm with Mobile Anchor Positioning (GA MAP). Root Mean Square Error (RMSE) has been used as a performance measure to compare between the two approaches namely, DE-MAP and GA-MAP. Simulation results demonstrate the fact that our proposed Differential Evolution with Mobile Anchor Positioning (DE-MAP) algorithm is effective in bringing down the localization error when compared to GA-MAP algorithm.