3D Localization in Large-Scale Wireless Sensor Networks: A Micro-Differential Evolution Approach

Most of the recent proposed approaches for sensor(mote) localization are focused on 2-D environments with limited functionalities. This is mostly due to the nature of problem which is non-linear, large-scale, and has limited hardware resources. The micro-evolutionary algorithms (MEAs) utilize a small-size population to solve optimization problems. Therefore, such algorithms require much less processing time and memory than standard evolutionary algorithms (EA), suitable for implementation on embedded systems. In this paper, a novel protocol for localization of motes in 3-D environments is proposed, simulated, and discussed. The localization problem is modeled as an optimization problem. The proposed model is based on a realistic approach to the localization problem, where possible errors and noises in the localization procedure such as signal strength detection are addressed. To present a suitable approach to solve the proposed optimization model, a comparative study on performance of the micro-differential evolution (MDE) algorithms is performed and the results are discussed.