启用SDN网络的应急流优先级

Jerico Moeyersons, Behrooz Farkiani, Bahador Bakhshi, S. A. MirHassani, T. Wauters, B. Volckaert, F. Turck
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引用次数: 6

摘要

紧急服务必须能够在不同的网络上以高优先级传输数据。5G引入了移动网络连接的切片概念,允许运营商为特定用例划分部分网络。此外,软件定义网络(SDN)原则允许为不同的网络切片分配不同的服务质量(QoS)级别。本文提出了一种基于sdn的解决方案,该方案在离线和在线上都可执行,它保证了应急流所需的带宽,并根据其优先级在剩余带宽上最大化了最佳努力流。离线模型允许针对一批流请求优化问题,但是计算成本很高,特别是流可以在并行路径上分割的变体。对于实际的动态情况,提出了一种在线方法,周期性地重新计算所有请求流的最优解,同时使用最短路径路由和贪婪启发式算法对中间流进行带宽分配。然后,通过模拟评估离线方法,同时通过SDN交换机的物理实验验证在线方法,这两种方法都是在500个最佳努力和50个应急流的场景中进行的。结果表明,离线算法能够保证应急流的资源分配,同时以亚秒级的执行时间优化最佳努力流。作为概念验证,带有Zodiac交换机的物理设置有效地验证了在线方法在现实设置中的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enabling Emergency Flow Prioritization in SDN Networks
Emergency services must be able to transfer data with high priority over different networks. With 5G, slicing concepts at mobile network connections are introduced, allowing operators to divide portions of their network for specific use cases. In addition, Software-Defined Networking (SDN) principles allow to assign different Quality-of-Service (QoS) levels to different network slices.This paper proposes an SDN-based solution, executable both offline and online, that guarantees the required bandwidth for the emergency flows and maximizes the best-effort flows over the remaining bandwidth based on their priority. The offline model allows to optimize the problem for a batch of flow requests, but is computationally expensive, especially the variant where flows can be split up over parallel paths. For practical, dynamic situations, an online approach is proposed that periodically recalculates the optimal solution for all requested flows, while using shortest path routing and a greedy heuristic for bandwidth allocation for the intermediate flows.Afterwards, the offline approaches are evaluated through simulations while the online approach is validated through physical experiments with SDN switches, both in a scenario with 500 best-effort and 50 emergency flows. The results show that the offline algorithm is able to guarantee the resource allocation for the emergency flows while optimizing the best-effort flows with a sub-second execution time. As a proof-of-concept, a physical setup with Zodiac switches effectively validates the feasibility of the online approach in a realistic setup.
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