Collaborative Diffusive Source Localization in Wireless Sensor Networks
The authors propose a collaborative, energy efficient method for diffusive source localization in wireless sensor networks. The algorithm is based on distributed and iterative Maximum-Likelihood (ML) estimation, which is very sensitive to initialization. As a part of the proposed method they present an approach for obtaining a "Good enough" initial value for the ML recursion based on infinite time approximation and semi-definite programming. They also present an approach for determining the sensor node that initiates the estimation process. To improve the convergence rate of the algorithm, they consider the case where selected nodes collaborate with their neighbors. Simulation results are used to characterize the performance and energy efficiency of the algorithm.