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Range-free 3D node localization in anisotropic wireless sensornetworks

Abstract

Abstract— In this paper, we propose two computationally efficient ‘range-free’ 3D node localization schemes usingthe application of hybrid-particle swarm optimization (HPSO) and biogeography based optimization(BBO). It is considered that nodes are deployed with constraints over three layer boundaries, in ananisotropic environment. The anchor nodes are randomly distributed over the top layer only and tar-get nodes distributed over the middle and bottom layers. Radio irregularity factor, i.e., an anisotropicproperty of propagation media and heterogenous properties of the devices are considered. To overcomethe non-linearity between received signal strength (RSS) and distance, edge weights between each targetnode and neighboring anchor nodes have been considered to compute the location of the target node.These edge weights are modeled using fuzzy logic system (FLS) to reduce the computational complexity.The edge weights are further optimized by HPSO and BBO separately to minimize the location error. Boththe proposed applications of the two algorithms are compared with the earlier proposed range-free algo-rithms in literature, i.e., the simple centroid method and weighted centroid method. The results of ourproposed applications of the two algorithms are better as compared to centroid and weighted centroidmethods in terms of error and scalability.

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