A Novel Controller Placement Using Petri-Nets for SDNs

Wael Hosny Fouad Aly
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Abstract

Software defined networking (SDN) separates the control and the data planes. This separation brings flexibility to the network. But the decoupling has some drawbacks such as the controller placement problem (CPP). Controller placement is a crucial task which affects the overall networks’ performance. This paper proposes a novel controller placement model that is based on petri-nets to place the SDN’s controllers. The proposed model is called controller placement using petri-nets for SDNs (CPPNSDN). CPPNSDN aims to reduce the average propagation latency among switches and their associated controllers. CPPNSDN divides the network into sub-networks. Each sub-network is governed by a controller. Experiments were conducted on the Internet2/OS3E topology to evaluate the performance of CPPNSDN. Experiments show that CPPNSDN reduces the average latency significantly compared to two reference models. The first reference model is the Modified Density Peaks Clustering (MDPC) and the Optimized Kmeans model. In terms of the overall average latency, the CPPNSDN has shown promising results as it outperformed the MDPC and optimized Kmeans reference models by 7% and 17% respectively. Confidence Interval (CI) used was 90%. This is an ongoing work and the results are promising for more future investigation.
基于Petri-Nets的新型sdn控制器布局
软件定义网络(SDN)将控制平面和数据平面分开。这种分离为网络带来了灵活性。但是这种解耦存在一些缺点,如控制器放置问题(CPP)。控制器的放置是影响整个网络性能的关键任务。本文提出了一种新的基于petri网的控制器放置模型来放置SDN的控制器。提出的模型称为使用petri-nets进行sdn (CPPNSDN)的控制器放置。CPPNSDN旨在降低交换机及其相关控制器之间的平均传播延迟。CPPNSDN将网络划分为多个子网。每个子网由一个控制器管理。在Internet2/OS3E拓扑上进行了实验,以评估CPPNSDN的性能。实验表明,与两种参考模型相比,CPPNSDN显著降低了平均延迟。第一个参考模型是改进的密度峰聚类(MDPC)和优化的Kmeans模型。在总体平均延迟方面,CPPNSDN表现出了令人满意的结果,它比MDPC和优化的Kmeans参考模型分别高出7%和17%。使用的置信区间(CI)为90%。这是一项正在进行的工作,其结果为未来更多的研究提供了希望。
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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