Joint Task Offloading and Flexible Functional Split in 5G Radio Access Network

Zhipeng Cheng, Yuliang Tang, Haijie Wu
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引用次数: 10

Abstract

Task offloading is a cost-effective way to allow users to obtain better service by offloading the computation intensive tasks to the fog or cloud computing nodes.Many previous work have been done and many of them focus on where to offload the task and how to split the task for cooperative execution.However,few of them consider task offloading in 5G flexible radio access network(F-RAN) and split the task according to the flexible functional split between the central unit(CU) and distributed unit(DU).In this paper, we study the task offloading in 5G F-RAN and combine the task split with flexible functional split. We firstly formulate a multiuser offloading decision problem as a energy consumption minimization problem which results in a trade-off between energy consumption and delay tolerance.In view of the characteristics of 5G F-RAN, the fronthaul and backhaul network are taken into consideration when calculating the energy consumption and delay. We split the task according to the flexible functional split between CU and DU for cooperative execution when the task is offloaded.Numerical simulations show that our proposed model can reduce the energy consumption and execution delay.
5G无线接入网中的联合任务卸载与灵活功能拆分
任务卸载是将计算密集型任务卸载到雾计算或云计算节点上,使用户获得更好服务的一种经济有效的方式。之前已经完成了许多工作,其中许多工作都集中在任务的卸载位置以及如何拆分任务以进行协同执行。然而,在5G灵活无线接入网(F-RAN)中,很少有人考虑任务卸载,并根据中央单元(CU)和分布式单元(DU)之间的灵活功能划分来划分任务。本文研究了5G F-RAN中的任务卸载问题,并将任务拆分与灵活功能拆分相结合。首先将多用户卸载决策问题表述为能量消耗最小化问题,该问题在能量消耗和延迟容忍度之间进行权衡。针对5G F-RAN的特点,在计算能耗和时延时考虑了前传和回程网络。我们根据CU和DU之间灵活的功能划分对任务进行拆分,以便在任务卸载时协同执行。数值仿真结果表明,该模型能够有效地降低能耗和执行延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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