Secure Task Offloading for Rural Area Surveillance Based on UAV-UGV Collaborations.

The increasing availability of autonomous Unmanned Aerial Vehicles (UAVs) has provided an emerging way for extensive surveillance and monitoring in civilian and military with the advantages of high flexibility, mobility, and bird's-eye features. To mitigate the limitations of on-board energy and computation capacity, UAVs usually offload intensive computation tasks (e.g., image/video processing) to base-station-enabled mobile-edge computing (MEC) facilities. However, base stations are not always available in rural areas. To this end, we propose to offload computation-intensive tasks to Unmanned Ground Vehicles (UGVs), which have fixed routes (i.e., highways and roads). However, the UAV-UGV wireless communication may disclose the offloading information to potential eavesdroppers. Besides, such UGVs have sufficient computation slots but may run out of the target area after a period of traveling. In this article, the tasks cached on UAVs are modeled as a stochastic queue, and a secure communication strategy to offload the cached tasks from UAVs to UGVs is proposed. We try to maximize the average utility of such a UAV-UGV collaboration with respect to latency, power, velocity, anti-collision, and distance. To solve this non-convex mixed integer nonlinear programming problem, a fast converging and computationally efficient iterative algorithm is investigated utilizing the block coordinate descent method and the successive convex approximation technique. Experiment results demonstrate that our algorithm consistently outperforms the state-of-the-art scheme, significantly improving the average utility of the system.