Localization Algorithm for Wireless Sensor Network Based on Genetic Simulated Annealing Algorithm

Abstract

In most sensor network applications, the information gathered by sensors will be meaningless without the location of the sensor nodes. Node localization has been a topic of active research in recent years. Accurate self-localization capability is highly desirable in wireless sensor network (WSN). This paper proposes a genetic simulated annealing algorithm based localization (GSAAL) algorithm for WSN. The proposed algorithm adopts two new genetic operators: single-vertex- neighborhood mutation and the descend-based arithmetic crossover. Four example problems are used to evaluate the performance of the proposed algorithm. Simulation results show that our algorithm can achieve higher accurate position estimation than semi-definite programming with gradient search localization (SDPL).