A precision adjustable trajectory planning scheme for UAV-based data collection in IoTs

With the increasing popularity of the IoTs (Internet of Things), the efficient data collection with Unmanned Aerial Vehicles (UAVs) is demanded by numerous applications. The technical challenge, which restricts the deployment of the UAVs, is the high latency of the data collection. In this paper, we focus on the problem of trajectory planning, specifically, determination of how the UAVs traverse through the sensing field and the scheduling of the communication tasks with the IoT nodes. We first ignore the energy consumpti on of IoT nodes but relax it eventually. Therefore, the trajectory planning problem can be formulated as a special case of the traveling salesman problem with neighborhoods (TSP-N). We propose a Precision Adjustable Trajectory Planning (PATP) scheme, which can calculate the k -communication area based on the stratified grid approach and shorten the traveling trajectory of the UAV by reducing the data collection sites, to enable a tradeoff between execution time and calculation precision. We then take the realistic energy consumption of wireless communications into account, which is one of the key questions in researches of IoTs, to extend the network lifetime with the On-Demand PATP (OD-PATP) scheme. The simulation results show that the PATP scheme can obtain a 15 % reduction in number of visiting point at least and the trajectory length obtained by the OD-PATP scheme can be shortened about 45 % .