Optimal Sensor Localization Using Evolutionary Computing Algorithms

In this paper, the location estimation of sensor nodes in wireless sensor networks is improved using optimization. The algorithms from the domain of evolutionary computing (EC) are used for reducing the error that occurs in the localization calculations. The EC-based algorithms are namely genetic algorithm (GA), cultural algorithm (CA), and differential evolution (DE) algorithm. All three algorithms use two parameters: the anchor coordinates obtained by a mobile anchor and the distance between the unknown nodes and anchor positions. The EC- based algorithms are used for optimizing the localization error. The maximum accurate results are shown by the DE algorithm, whereas CA is the fastest among the three algorithms. The performance of the DE and GA is similar in terms of accuracy but varies in the delay.