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Joint Service Placement and Request Routing in Multi-cell Mobile Edge Computing Networks

机译:多单元移动边缘计算网络中的联合服务放置和请求路由

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The proliferation of innovative mobile services such as augmented reality, networked gaming, and autonomous driving has spurred a growing need for low-latency access to computing resources that cannot be met solely by existing centralized cloud systems. Mobile Edge Computing (MEC) is expected to be an effective solution to meet the demand for low-latency services by enabling the execution of computing tasks at the network-periphery, in proximity to end-users. While a number of recent studies have addressed the problem of determining the execution of service tasks and the routing of user requests to corresponding edge servers, the focus has primarily been on the efficient utilization of computing resources, neglecting the fact that non-trivial amounts of data need to be stored to enable service execution, and that many emerging services exhibit asymmetric bandwidth requirements. To fill this gap, we study the joint optimization of service placement and request routing in MEC-enabled multi-cell networks with multidimensional (storage-computation-communication) constraints. We show that this problem generalizes several problems in literature and propose an algorithm that achieves close-to-optimal performance using randomized rounding. Evaluation results demonstrate that our approach can effectively utilize the available resources to maximize the number of requests served by low-latency edge cloud servers.
机译:增强现实,网络游戏和自主驾驶等创新的移动服务的扩散促使对计算资源的低延迟访问不断增长,这些资源不能仅由现有的集中云系统遇到。预计移动边缘计算(MEC)将是通过在网络外围的计算机外围执行计算任务的执行来满足低延迟服务的需求,以邻近最终用户来实现对低延迟服务的需求。虽然最近的一些研究已经解决了确定服务任务的执行和用户请求的路由的问题,但是该焦点主要是在有效利用计算资源,忽略了非琐碎量的事实需要存储数据以实现服务执行,并且许多新兴服务表现出不对称的带宽要求。为了填补这个差距,我们研究了具有多维(存储 - 计算 - 通信)约束的MEC的多单元网络中的服务放置和请求路由的联合优化。我们表明,此问题概括了文献中的几个问题,并提出了一种算法,可以使用随机舍入实现近似最佳性能。评估结果表明,我们的方法可以有效地利用可用资源来最大化低延迟边缘云服务器所服务的请求数量。

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