PTSP Solution Strategy for Motion Trajectory of UAV in Ubiquitous Sensor Network

Nowadays, thanks to technological progress, the Unmanned Aerial Vehicles (UAVs) have appeared and allow to realize practical applications at lower costs with higher quality. These are widely used in the ubiquitous sensor networks USN. To improve their performance, it is interesting to plan their complex missions in reasonable solution times. In this paper we propose a modeling of the UAV motion in USN as being a Probabilistic Traveling Salesman Problem (PTSP), where the number of sensors to be served each time is a random variable. This method consists in optimizing the movement trajectory of the UAV in order to reduce the time for delivery of information to the users. This modeling makes it possible to recover the essential information of the system despite the disturbance of a subset of its elementary components, while ensuring the resolution of the addressed situation according to the a priori strategy of the PTSP. It ensures the existence of a solution adaptable to a multitude of TSPs in real time. We proposed numerical results based on exact Branch and Bound algorithm that provides an optimal solution through each set of sensors which occur with certain probabilities.