Optimized Energy-Efficient Iterative Distributed Localization for Wireless Sensor Networks

Location information of sensor nodes deployed in the mission field plays an important role on the performance of Wireless Sensor Networks (WSNs). It is highly desirable to develop localization systems by keeping in mind WSN constraints and its location estimation capability. Optimization algorithms have proven to be good candidates for quality of position estimation. Flip ambiguity is one of the major challenges in such techniques. In this paper two types of constraints are proposed to overcome this problem. Particle Swarm Optimization (PSO) in conjunction with the proposed constraints is used iteratively in distributed manners to localize blind nodes in the WSN. Simulation results show that the proposed technique overcomes the problem of flip ambiguity and is resource efficient as well. The proposed technique mitigates 95 percent (worst-case) to 100 percent (best-case) flips and saves 80 percent (worst-case) to 87 percent (best-case) energy as compared to the previous technique available in the literature.