Recently, unmanned aerial vehicles (UAVs) assisted multi-access edge computing (MEC) systems emerged as a promising solution for providing computation services to mobile users outside of terrestrial infrastructure coverage. As each UAV operates independently, however, it is challenging to meet the computation demands of the mobile users due to the limited computing capacity at the UAV's MEC server as well as the UAV's energy constraint. Therefore, collaboration among UAVs is needed. In this paper, a collaborative multi-UAV-assisted MEC system integrated with a MEC-enabled terrestrial base station (BS) is proposed. Then, the problem of minimizing the total latency experienced by the mobile users in the proposed system is studied by optimizing the offloading decision as well as the allocation of communication and computing resources while satisfying the energy constraints of both mobile users and UAVs. The proposed problem is shown to be a non-convex, mixed-integer nonlinear problem (MINLP) that is intractable. Therefore, the formulated problem is decomposed into three subproblems: i) users tasks offloading decision problem, ii) communication resource allocation problem and iii) UAV-assisted MEC decision problem. Then, the Lagrangian relaxation and alternating direction method of multipliers (ADMM) methods are applied to solve the decomposed problems, alternatively. Simulation results show that the proposed approach reduces the average latency by up to 40.7\% and 4.3\% compared to the greedy and exhaustive search methods.
翻译:最近,无人驾驶飞行器(无人驾驶飞行器)协助的多接入边缘计算系统(MEC)成为向地面基础设施覆盖范围以外的移动用户提供计算服务的有希望的解决办法,然而,由于每个无人驾驶飞行器独立运作,由于无人驾驶飞行器的MEC服务器的计算能力有限以及无人驾驶飞行器的能源限制,满足移动用户的计算需求具有挑战性,因此无人驾驶飞行器(UAV)协助的多接入边缘计算系统(MEC)是向地面基础设施覆盖的地面基地站(BS)提供计算服务的有希望的解决方案。随后,通过优化卸载决定以及分配通信和计算资源,满足移动用户和无人驾驶飞行器的能源限制,对无人驾驶飞行器之间需要协作。因此,本文件提出了与MEC启动的地面基地站(BS)整合的多功能性多功能辅助MEC系统(UC)协作的多功能系统。随后,通过优化对移动用户在拟议系统中遇到的不透明性定位问题、不断升级的搜索方法,以及不断升级的MAAFLA方法,将决定分配问题降低平级方法。