This letter studies hierarchical Mobile Edge Computing (MEC) with multiple sources, multiple buffer-aided relays, and one Higher-level computing Node (HN). The relays may or may not have computation resources and therefore, they randomly decide to process the received tasks or to offload them to the HN. We consider the delay in the transmission and computation buffers, and propose a novel Fairness and Efficiency Cost Function (FECF) as the weighted sum of the maximum Average Response Time (ART) and the overall system ART. We formulate a novel problem to minimize the FECF while keeping the system queues stable, by jointly optimizing the offloading probabilities at the relays and the capacities of the virtual machines at the HN. We prove that the problem is a multi-convex optimization problem and propose an effective solution method by alternating optimization. Simulation results demonstrate the effectiveness of the different variants of the proposed scheme in the scenarios with server-less and server-empowered relays and provide important insights regarding the fairness and efficiency in terms of the ART.

中文翻译：

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随机缓冲辅助中继辅助 MEC 的公平性和效率


这封信研究了具有多个源、多个缓冲辅助中继和一个高级计算节点 (HN) 的分层移动边缘计算 (MEC)。中继可能有也可能没有计算资源，因此它们随机决定处理接收到的任务或将它们卸载到 HN。我们考虑传输和计算缓冲区中的延迟，并提出一种新颖的公平和效率成本函数（FECF）作为最大平均响应时间（ART）和整个系统ART的加权和。我们提出了一个新问题，通过联合优化中继处的卸载概率和 HN 处虚拟机的容量，在保持系统队列稳定的同时最小化 FECF。我们证明该问题是一个多凸优化问题，并提出了一种有效的交替优化求解方法。仿真结果证明了所提出方案的不同变体在无服务器和服务器授权中继场景中的有效性，并提供了有关 ART 公平性和效率的重要见解。