Range-free 3D node localization in anisotropic wireless sensor networks
Propose two computationally effective range-free (RF) 3D node localization schemes using applications of biogeography based optimization (BBO) and hybrid particle swarm optimization (HPSO) for anisotropic wireless sensor networks. Nodes are randomly deployed with constraints over three layer boundaries. The anchor nodes are randomly distributed over top layer only and target nodes are distributed over the middle and bottom layers. Non-linearity between received signal strength (RSS) and distance is modeled using fuzzy logic system (FLS) to reduce the computational complexity and further optimized by HPSO and BBO to minimize the error. Knowledge based edge weight of the anchor node to determine the accurate coordinates of the target node. A novel proximity based performance index, to evaluate the proposed schemes.
biogeography based optimization (bbo) fuzzy logic system (fls) hybrid-particle swarm optimization (hpso) wireless sensor networks (wsns) radio irregular model (rim)