A novel data collector path optimization method for lifetime prolonging in wireless sensor networks
Due to the limited battery capacity, the lifetime and performance of the battery-powered WSNs are constrained. In order to prolong the lifetime, applying mobile data collectors to gather data in WSNs is a promising approach. In this paper, we design a two-phase data gathering strategy with the mobile data collector in the cluster-based WSN to improve energy efficiency and satisfy the delay constraints. More precisely, the sensors are divided into a set of clusters in the first phase, which ensures that the sensors can communicate with the mobile data collector within predetermined hops. We then develop the path for the mobile data collector using a genetic algorithm that is an applicable strategy for the optimization problem with respect to the shortest path finding in the large-scale WSNs. We evaluate the performance of the proposed path planning protocol by conducting intensive simulations. The simulation results indicate that the proposed scheme outperforms some state-of-the-art techniques on energy efficiency while enhancing the data update rate.
