An Evolutionary Multipath Routing Algorithm using SDN

Noel Farrugia, J. A. Briffa, Victor Buttigieg
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引用次数: 4

Abstract

The centralisation of the control plane in the Software Defined Network (SDN) architecture allows the implementation of a globally optimised multipath routing algorithm, something that is not possible in traditional distributed networks. In our previous work, we have already shown a performance improvement made possible by SDN when using Linear Programming (LP) to find the optimal routing solution as compared to OSPF and ECMP. However, while multipath routing may be required to utilise a network to its maximum capacity, this may cause packet re-ordering, which negatively affects TCP performance. To overcome this limitation and improve TCP performance at a flow level, in this work we replace the LP routing algorithm with a multi-objective genetic algorithm to solve the Multi Commodity Flow problem. This also resolves the scalability problem in LP, and additionally allows us to choose good solutions that offer the smallest number of flow splits whilst maintaining a good compromise in terms of the total network flow and the total cost of the selected paths. While the chosen solution may not offer the best overall network usage, it improves performance at the flow level because the packet reordering problem is reduced.
基于SDN的进化多径路由算法
软件定义网络(SDN)架构中控制平面的集中化允许实现全局优化的多路径路由算法,这在传统的分布式网络中是不可能的。在我们之前的工作中,我们已经展示了与OSPF和ECMP相比,当使用线性规划(LP)找到最佳路由解决方案时,SDN可能带来的性能改进。然而,虽然多路径路由可能需要利用网络的最大容量,但这可能会导致数据包重新排序,从而对TCP性能产生负面影响。为了克服这一限制并提高TCP在流量水平上的性能,在这项工作中,我们用多目标遗传算法取代LP路由算法来解决多商品流问题。这也解决了LP中的可扩展性问题,并且还允许我们选择好的解决方案,提供最小数量的流分裂,同时在总网络流量和所选路径的总成本方面保持良好的折衷。虽然所选择的解决方案可能不能提供最佳的整体网络使用,但它可以提高流级别的性能,因为减少了数据包重新排序问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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