Energy-efficient UAV Trajectory Optimization for Securing Data Collection

Due to fully controllable mobility and on-demand deployment, despatching unmanned aerial vehicles (UAVs) to collect sensing data from distributed sensor nodes (SNs) is an emerging application in the Internet of Things. To jointly deal with the data security and energy limitation in UAV-enabled wireless sensor networks, the energy-efficient trajectory optimization for UAV data collections is investigated based on the framework of physical layer security. The performance metric of secrecy energy efficiency (EE) is maximized by using the optimization approaches of fractional programming and sequential convex approximation. A solution scheme based on the two optimization approaches is addressed, which transform the primal optimization problem into a series of convex subproblems. In essence, the primal optimization problem is solved by iterative loop, and at each iteration a convex subproblem is solved by some available convex optimization algorithm. Finally, to further improve the secrecy EE, a SN selection strategy is proposed to activate the SNs with a higher secrecy rate than a threshold to transmit data while the others keep sleeping for energy saving. Simulation results show that, compared with the shortest trajectory, the energy-efficient trajectory obtained by the proposed scheme can achieve a higher secrecy EE.