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PARS-SR: A scalable flow forwarding scheme based on Segment Routing for massive giant connections in 5G networks

机译:PARS-SR:基于5G网络中大规模巨型连接的段路由的可扩展流转发方案

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摘要

In 5G networks with SDN architecture, the traffic explosion and the rising of diverse service requirements lead to many challenges for 5G core networks on flexibility and scalability. In order to achieve high-speed forwarding of traffic and diversified transmission requirements in the 5G era, combined with SDN and Segment Routing, we propose a scalable flow forwarding scheme called Segment Routing based on Path Aggregation and Rule sharing (PARS-SR) to solve SDN switch flow table resource shortage problem. Traditional OpenFlow-based or MPLS-based flow forwarding scheme may lead to performance degradation due to flow-table overflowed or heavy MPLS label load incurred. PARS-SR exploits SDN, Segment Routing and intelligent path encoding algorithm to achieve a trade-off between flow table resource and MPLS label load. The proposed PARS-SR can learn the flow path information online to implement path aggregation and rule sharing by aggregating a large number of flows into a small number of flow entries based on the coincidence degree of the flow path. To find the optimal flow path aggregation scheme, we present an intelligent encoding algorithm to maximize the overall cost saving. The simulation results show that PARS-SR can effectively reduce both the number of flow entries and the MPLS label load of the packet.
机译:在具有SDN架构的5G网络中,流量爆炸和多样化服务需求的上升导致5G核心网络对灵活性和可扩展性的许多挑战。为了实现5G时代的流量和多元化传输要求的高速转发,结合SDN和段路由,我们提出了一种基于路径聚合和规则共享(PARS-SR)来解决的分段路由的可扩展流转发方案SDN交换机流表资源短缺问题。传统的基于Openflow的或基于MPLS的流发型方案可能导致由于流动表溢出或繁重的MPLS标签负载而导致性能下降。 PARS-SR利用SDN,段路由和智能路径编码算法,实现流表资源和MPLS标签负载之间的权衡。所提出的PARS-SR可以在线学习流路信息以实现路径聚合和规则共享,通过基于流动路径的重合度聚合到少量的流条目中来实现进入少量流动条目。为了找到最佳流路聚合方案,我们介绍了一种智能编码算法,可以最大化整体成本节省。仿真结果表明,PARS-SR可以有效地减少数据包的流动条目数和MPLS标签负载。

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