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Centralized vs. distributed algorithms for resilient 5G access networks

机译:弹性5G接入网络的集中式算法与分布式算法

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摘要

Cloud radio access networks (C-RANs), relying on network function virtualization and software-defined networking (SDN), require a proper placement of baseband functionalities (BBUs) to reach full coverage of served areas and service continuity. In this context, network resources can be shared and orchestrated to meet the flexibility required by a dynamically evolving environment. Different methodologies, based on analytical formulation or heuristic algorithms, can be applied to achieve suitable trade-offs among cost components. This paper considers both centralized and distributed algorithms to obtain BBU hotel placement in C-RAN and compares their performance, scalability and adaptability to evolving scenarios. As expected, the results obtained with the distributed approach are sub-optimal, but very close, in most cases, to the optimal solutions obtained with a centralized algorithm based on integer linear programming. In addition to off-loading the SDN orchestrator, the distributed approach, differently from the centralized one, is shown to be able to cope with the evolution of the C-RAN topology with limited incremental changes in the original placement. The limits of the centralized approach in terms of scalability that the distributed approach is able to overcome are also evidenced.
机译:依靠网络功能虚拟化和软件定义网络(SDN)的云无线电接入网络(C-RAN)需要正确放置基带功能(BBU)才能完全覆盖服务区域和服务连续性。在这种情况下,可以共享和协调网络资源,以满足动态变化的环境所需的灵活性。可以应用基于分析公式或启发式算法的不同方法,以实现成本要素之间的适当权衡。本文考虑了集中式和分布式算法来获取C-RAN中BBU酒店的位置,并比较了它们在性能,可伸缩性和适应不断变化的场景中的适应性。不出所料,使用分布式方法获得的结果不是最优的,但在大多数情况下,非常接近使用基于整数线性规划的集中式算法获得的最优解。除了减轻SDN编排器的负担外,与集中式管理器不同,分布式方法显示出能够应对C-RAN拓扑的发展,并且原始布局中的增量变化有限。还证明了集中式方法在分布式方法能够克服的可伸缩性方面的局限性。

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