Joint Optimization of Trajectory and Node Access in UAV-Aided Data Collection System

Abstract

With the continuous development of Internet of Things, data transmission presents an exponential rising trend. Due to the limited energy storage and low transmission power of sensor nodes, it is impossible to continuously transmit a large amount of collected data to the remote cloud center for a long time. To guarantee the data reliability and extend the lifetime of sensor nodes, we use unmanned aerial vehicle (UAV) assisted data collection for data transmission to improve the performance of the network. As each sensor node has a certain business requirement for unloaded data volume, the flight trajectory and node access scheme are jointly optimized to minimize the energy consumed by all the sensing nodes. First, a model regarding the minimization problem of the maximum energy consumption was constructed. To effectively solve this nonconvex problem, the block coordinate descent method and slack variable method are used to transform the original optimization problem into two subproblems: trajectory optimization problem and node access scheme optimization problem. Second, an algorithm is proposed using the successive convex approximation to jointly optimize the flight trajectory and node access scheme. This algorithm acquires the optimal node access scheme and UAV flight trajectory successively in each iteration. When the number of iterations is great enough, the minimum–maximum energy consumption of sensing nodes is gradually converged. The simulation results showed that in comparison with the basic UAV flight scheme, the proposed algorithm can effectively reduce the energy consumption of nodes and improve the data transmission rate, and meanwhile, this algorithm is characterized by favorable convergence and tolerable complexity.