Parallel Firefly Algorithm for Localization Algorithm in Wireless Sensor Network

Node localization has been a very active research topic in recent years. Accurate self-localization capability is highly desirable in wireless sensor network (WSN). In this paper, a node localization algorithm based on the received signal strength (RSS) measurements and Parallel Firefly Algorithm (PFA) in Wireless Sensor Networks (WSN) is proposed. By fully considering the distance factor, an improved objective function is defined, so the node localization problem in WSN could be transformed into a nonlinear unconstrained optimization problem. Giving the distances between a sensor and a few of its 1-hop neighbors, the proposed algorithm can estimate the sensor positions using Parallel Firefly Algorithm. Simulation results show that the proposed method can achieve better results than those obtained from the Particle Swarm Optimization (PSO), the Genetic Algorithm (GA) and the original methods in accuracy.