Fuzzy logic based 3D localization in wireless sensor networks using invasive weed and bacterial foraging optimization

The purpose of this paper is to improve the performance of node localization in 3D space for wireless sensor network. To achieve this objective, we propose two range free localization algorithms for 3D space in anisotropic environment using the application of bacterial foraging optimization (BFO) and invasive weed optimization (IWO). In proposed methods, only received signal strength (RSS) information between nodes is sufficient for estimating target nodes locations. The RSS information gives clue to find out the distances between target nodes and anchor nodes. To overcome the non-linearity between RSS and distance, edge weights between target nodes and their neighbouring anchor nodes are considered to estimate the positions of target nodes. To further reduce the computational complexity and to model the edge weights, we use fuzzy logic system in this paper. BFO and IWO techniques are used to further optimize the edge weights separately to achieve the better localization accuracy. The simulation results show the superiority of the proposed algorithms as compared to centroid method, weighted centroid and existing 3D localization algorithms in terms of localization accuracy, stability, positioning coverage and scalability.