有限回程移动云计算的联合上行/下行和卸载优化

A. Al-Shuwaili, Alireza Bagheri, O. Simeone
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引用次数: 5

摘要

移动云计算可以将计算量大的应用程序(如游戏、对象识别或视频处理)从移动用户(mu)卸载到连接到无线接入点的云服务器上。移动云计算系统操作的优化相当于最小化在应用层延迟约束下跨所有mu卸载所需的能量的问题。在多个mu通过共享无线介质跨多个cell传输的场景中,该问题需要对上行链路和下行链路进行干扰管理,上行链路通过mu卸载云计算所需的数据,下行链路通过mu将云计算的结果反馈给mu,以及分配用于无线边缘与云之间通信的回程资源和云上的计算资源。在本文中,这个问题是为一般的多天线,或MIMO,信道,并解决了逐次凸逼近方法。数值结果说明了计算资源和通信资源联合分配的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint uplink/downlink and offloading optimization for mobile cloud computing with limited backhaul
Mobile cloud computing enables the offloading of computationally heavy applications, such as for gaming, object recognition or video processing, from mobile users (MUs) to a cloud server connected to wireless access points. The optimization of the operation of a mobile cloud computing system amounts to the problem of minimizing the energy required for offloading across all MUs under latency constraints at the application layer. In a scenario with multiple MUs transmitting over a shared wireless medium across multiple cells, this problem requires the management of interference for both the uplink, through which MUs offload the data needed for computation in the cloud, and for the downlink, through which the outcome of the cloud computation are fed back to the MUs, as well as the allocation of backhaul resources for communication between wireless edge and cloud and of computing resources at the cloud. In this paper, this problem is formulated for general multi-antenna, or MIMO, channels, and tackled by means of successive convex approximation methods. The numerical results illustrate the advantages of a joint allocation of computing and communication resources.
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