Heuristic mobile data gathering for wireless sensor networks via trajectory control

This article focuses on the problem of scheduling the optimal paths of multiple mobile elements (e.g. robots, vehicles, etc.) to minimize the travel distance and balance the energy consumption and the data gathering latency in wireless sensor networks for smart cities. To partition the network for the multiple mobile elements and compute the trajectories of the multiple mobile elements, we utilize the sensor's communication range and construct a multiple mobile elements scheduling problem. A heuristic mobile data gathering approach is proposed to solve this problem, which includes the following three steps. The sensor nodes are preliminarily partitioned into four levels, and then the clusterheads are further partitioned, and the traveling tour is scheduled for each cluster. After the first two steps, all the sensor nodes are partitioned reasonably for the multiple mobile elements. In the last step, the traveling tour is scheduled for each cluster, and the meeting point of each clusterhead is determined. We compare the proposed heuristic mobile data gathering with the existing approaches. The results indicate that the travel distance and the data gathering latency are reduced significantly, which further validates that the communication range is beneficial to minimize the travel distance.