Energy Efficient Resource Allocation and Computation Offloading Strategy in a UAV-enabled Secure Edge-Cloud Computing System

Abstract

Mobile edge computing (MEC) emerged as a promising approach for resource constrained devices due to its inherent capability to bring the cloud functionalities at the net-work edge. This paper jointly investigates the resource allocation and computation offloading problem in unmanned aerial vehicle (UAV) enabled secure edge-cloud computing system, where each computational task can be executed locally, offloaded to the MEC server, offloaded to the cloud server or offloaded to another UAV. To preserve security, we encrypt each computational task by employing highly dispersive chaotic substitution Box (S-Box). We formulate the original problem as an energy consumption minimization problem and propose two heuristic algorithms to solve it. We divide the original problem into three sub-problems, i.e., resource allocation sub-problem, task partition sub-problem and computation offloading sub-problem, and solve them accordingly to obtain the energy efficient resource allocation and computation offloading strategies. Finally, simulation results demonstrate the effectiveness of the proposed scheme when compared with related schemes.