Energy-Aware Computation Offloading and Routing Strategy for Multi-UAV-assisted Mobile Edge Computing

Multi-Unmanned Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) technology can provide users with more flexible and efficient computing services. Most of the existing research works realize multi-UAV collaboration through single-hop or multi-hop task relaying. Although the delay and energy consumption incurred in transmitting mission results to the destination node is relatively small, the UAV node changes dynamically and the result feedback should not be ignored. At the same time, when the remaining power of the UAVs swarms is unevenly distributed, when one UAV runs out of power, the users in the area it serves will fall into congestion again. In order to solve these problems, we propose an energy-aware computation offloading and routing (ECOR) strategy with result feedback. ECOR allows tasks to select the best node by flying ad-hoc network (FANET) multi-hop routing, thus increasing the lifetime of the entire network and the number of tasks completed during the lifetime, i.e., the lifetime value. Meanwhile, we propose to embed the remaining energy and reliability information of the UAV in the Hello message, thus making the UAV energy-aware. Considering the dynamics of the environment and the complexity of the optimization objective, we propose to use Dueling DQN to optimize offloading and routing decisions. After the task is successfully offloaded, the system will enter the result transmission phase to relay the task result to the destination node. Simulation results show that ECOR significantly outperforms other strategies in terms of cumulative rewards, energy efficiency, and task delivery rates.