将网管信息集成到SDN控制平面

Stanislav Lange, Lorenz Reinhart, T. Zinner, D. Hock, N. Gray, P. Tran-Gia
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引用次数: 2

摘要

通过软件定义网络(SDN),运营商可以从其网络的更高灵活性、成本效率和可编程性中受益。由于现代网络由大量异构设备组成,还包括非sdn遗留设备,因此经常使用网络管理系统(nms)来监视和配置网络。尽管SDN控制器和NMS都有一个集中的网络视图,但它们在不同的时间尺度上运行,处理不同粒度级别的信息。在这项工作中,我们研究了当NMS定期向SDN控制器提供信息时对网络性能的影响。为此,我们设计、实现并比较了三种基于ONOS控制器的交互机制。它们代表了关于结果系统的复杂性及其性能的不同权衡。除了默认的ONOS控制器之外,我们还开发了两个扩展版本。其中一个在等成本路径上执行基于哈希的负载平衡,而另一个通过ONOS的意图和注释框架利用外部NMS信息来优化控制平面决策。除了在使用优化控制器时显示显着性能改进的评估之外,我们还提出了一个参数研究,强调了网络特征(如流间隔到达时间、流持续时间和活动流数量)对性能的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating network management information into the SDN control plane
With software defined networking (SDN), operators benefit from a higher flexibility, cost efficiency, as well as programmability of their networks. Since modern networks are comprised of a multitude of heterogeneous devices and also include non-SDN legacy devices, network management systems (NMSs) are often used in order to monitor and configure the network. Although both, the SDN controller and the NMS, have a centralized view of the network, they operate at different time scales and deal with information at different levels of granularity. In this work, we investigate the impact on the network performance when an NMS regularly provides information to an SDN controller. To this end, we design, implement, and compare three interaction mechanisms based on the ONOS controller. These represent different trade-offs regarding the complexity of the resulting system and its performance. In addition to the default ONOS controller, we develop two extended versions. One performs hash-based load balancing on equal cost paths while the other utilizes external NMS information via ONOS's intent and annotation framework to optimize control plane decisions. In addition to evaluations that show a significant performance improvement when using the optimized controllers, we present a parameter study that highlights the performance impact of network characteristics like the flow interarrival time, the flow duration, and the number of active flows.
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