On Reconfiguring 5G Network Slices

IF 13.8 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal on Selected Areas in Communications Pub Date : 2020-04-13 DOI:10.1109/JSAC.2020.2986898
Matteo Pozza, Patrick K. Nicholson, D. Lugones, Ashwin Rao, H. Flinck, S. Tarkoma
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引用次数: 16

Abstract

The virtual resources of 5G networks are expected to scale and support migration to other locations within the substrate. In this context, a configuration for 5G network slices details the instantaneous mapping of the virtual resources across all slices on the substrate, and a feasible configuration satisfies the Service-Level Objectives (SLOs) without overloading the substrate. Reconfiguring a network from a given source configuration to the desired target configuration involves identifying an ordered sequence of feasible configurations from the source to the target. The proposed solutions for finding such a sequence are optimized for data centers and cannot be used as-is for reconfiguring 5G network slices. We present Matryoshka, our divide-and-conquer approach for finding a sequence of feasible configurations that can be used to reconfigure 5G network slices. Unlike previous approaches, Matryoshka also considers the bandwidth and latency constraints between the network functions of network slices. Evaluating Matryoshka required a dataset of pairs of source and target configurations. Because such a dataset is currently unavailable, we analyze proof of concept roll-outs, trends in standardization bodies, and research sources to compile an input dataset. On using Matryoshka on our dataset, we observe that it yields close-to-optimal reconfiguration sequences 10X faster than existing approaches.
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论5G网络切片的重构
5G网络的虚拟资源有望扩展并支持迁移到基板内的其他位置。在这种情况下,5G网络切片的配置详细说明了虚拟资源在基片上的瞬时映射,并且可行的配置满足服务水平目标(Service-Level Objectives, slo),而不会使基片过载。将网络从给定的源配置重新配置为期望的目标配置涉及识别从源到目标的可行配置的有序序列。所提出的寻找这样一个序列的解决方案是针对数据中心进行优化的,不能原样用于重新配置5G网络切片。我们提出了一种分而治之的方法,用于寻找一系列可用于重新配置5G网络切片的可行配置。与以前的方法不同,Matryoshka还考虑了网络切片的网络功能之间的带宽和延迟约束。评估俄罗斯套娃需要一个源和目标配置对的数据集。因为这样的数据集目前是不可用的,我们分析概念推出的证明、标准化机构的趋势和研究来源来编译输入数据集。在我们的数据集上使用Matryoshka时,我们观察到它产生接近最优的重构序列的速度比现有方法快10倍。
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来源期刊
CiteScore
30.00
自引率
4.30%
发文量
234
审稿时长
6 months
期刊介绍: The IEEE Journal on Selected Areas in Communications (JSAC) is a prestigious journal that covers various topics related to Computer Networks and Communications (Q1) as well as Electrical and Electronic Engineering (Q1). Each issue of JSAC is dedicated to a specific technical topic, providing readers with an up-to-date collection of papers in that area. The journal is highly regarded within the research community and serves as a valuable reference. The topics covered by JSAC issues span the entire field of communications and networking, with recent issue themes including Network Coding for Wireless Communication Networks, Wireless and Pervasive Communications for Healthcare, Network Infrastructure Configuration, Broadband Access Networks: Architectures and Protocols, Body Area Networking: Technology and Applications, Underwater Wireless Communication Networks, Game Theory in Communication Systems, and Exploiting Limited Feedback in Tomorrow’s Communication Networks.
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