Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) has been considered as a promising approach to offering extensive coverage and massive computing capacities for Internet of Things (IoT). In this letter, we propose a novel multi-UAV-assisted multi-access MEC model by allowing each IoT user to offload task bits to multiple MEC servers deployed at UAVs simultaneously for parallel computing, which can effectively reduce the energy consumption of users and UAVs. The weighted sum energy consumption of UAVs and users is minimized by jointly optimizing the bit allocation, transmit power, CPU frequency, bandwidth allocation and UAVs’ trajectories. Due to the non-convexity of the formulated problem, it is decomposed into two subproblems and a joint resource allocation and trajectory design algorithm is proposed by alternative optimization. Simulation results show that our proposed algorithm with multiple radio access outperforms the fixed trajectory, fixed bandwidth allocation and the single access schemes.

中文翻译：

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多无人机辅助多接入移动边缘计算的联合资源分配和轨迹优化

无人机 (UAV) 辅助的移动边缘计算 (MEC) 被认为是一种为物联网 (IoT) 提供广泛覆盖和海量计算能力的有前途的方法。在这封信中，我们提出了一种新的多无人机辅助多接入 MEC 模型，通过允许每个 IoT 用户将任务比特卸载到同时部署在无人机上的多个 MEC 服务器进行并行计算，可以有效降低用户和无人机的能耗. 通过联合优化比特分配、发射功率、CPU频率、带宽分配和无人机的轨迹，使无人机和用户的加权总能耗最小化。由于公式化问题的非凸性，将其分解为两个子问题，并通过交替优化提出联合资源分配和轨迹设计算法。