Mobile edge computing (MEC) enables resource-limited IoT devices to complete computation-intensive or delay-sensitive task by offloading the task to adjacent edge server deployed at the base station (BS), thus becoming an important technology in 5G and beyond. Due to channel occlusion, some users may not be able to access the computation capability directly from the BS. Confronted with this issue, many other devices in the MEC system can serve as cooperative nodes to collect the tasks of these users and further forward them to the BS. In this paper, we study a MEC system in which multiple users continuously generate the tasks and offload the tasks to the BS through a cooperative node. As the tasks are continuously generated, users should simultaneously execute the task generation in the current time frame and the task offloading of the last time frame, i.e. the task is processed in a streaming model. To optimize the power consumption of the users and the cooperative node for finishing these streaming tasks, we investigate the duration of each step in finishing the tasks together with multiuser offloading ratio and bandwidth allocation within two cases: the BS has abundant computation capacity (Case I) and the BS has limited computation capacity (Case II). For both cases, the formulated optimization problems are nonconvex due to fractional structure of the objective function and complicated variable coupling. To address this issue, we propose optimal solution algorithm with low complexity. Finally, simulation is carried out to verify the effectiveness of the proposed methods and reveal the performance of the considered system.

翻译：移动边缘计算（MEC）通过将计算密集型或时延敏感型任务卸载至基站部署的邻近边缘服务器，使资源受限的物联网设备能够完成此类任务，从而成为5G及未来通信系统中的关键技术。由于信道遮挡，部分用户可能无法直接获取基站的计算能力。针对这一问题，MEC系统中的其他设备可作为协作节点，收集这些用户的任务并转发至基站。本文研究一个多用户连续生成任务并通过协作节点卸载至基站的MEC系统。由于任务是连续生成的，用户需同时执行当前时隙的任务生成与上一时隙的任务卸载，即采用流式处理模型。为优化用户与协作节点完成这些流式任务的功耗，我们研究了两种场景下完成任务的各阶段时长、多用户卸载比例及带宽分配问题：基站计算能力充裕（情况I）与基站计算能力受限（情况II）。由于目标函数的分数结构与变量复杂耦合，两类场景的优化问题均为非凸问题。针对此问题，我们提出低复杂度的最优求解算法。最后通过仿真验证所提方法的有效性，并揭示所研究系统的性能表现。