Localization in Wireless Sensor Networks Using Invasive Weed Optimization Based on Fuzzy Logic System

In this paper, a computationally efficient range-free localization algorithm in 2D plane has been proposed for wireless sensor networks using fuzzy logic system (FLS) and invasive weed optimization (IWO). The received signal strength (RSS) value is used to find out the distance between nodes in the network. To reduce the nonlinearity between RSS values and distances between nodes, and to model the edge weight of the anchor nodes based on the RSS value, FLS is used. Further IWO is used to optimize the edge weights of anchors to achieve the high localization accuracy. Radio propagation is considered as circular for all nodes in the proposed method. It is observed from the simulation results, proposed algorithm performs better in localization accuracy than some existing range free localization algorithms, i.e. centroid method, weighted centroid and range-free localization based on biogeography-based optimization.