Localization Algorithm in Wireless Sensor Networks Based on KH-SVM

摘要

Sensor node localization is one of research hotspots in the applications of wireless sensor networks (WSNs) field. A localization algorithm based on improved Support Vector Machine (SVM) for WSNs is proposed in this paper. SVM classification accuracy is the key to the localization accuracy. The selection of parameters is the important factor that influences the performance of SVM. Therefore, this paper proposes a parameter optimization algorithm based on Krill-herd algorithm (KH-SVM). The experimental results show that KH-SVM algorithm has better searching optimization ability compared with other optimization algorithms, such as Particle Swarm Optimization, Genetic Algorithm. Through the simulations, the performance of localization based on KH-SVM is evaluated. The results prove that it has higher accuracy than existing localization algorithm based on SVM. Finally, the limitation of the proposed localization algorithm is discussed and future work is present.