An Effective Clustering Algorithm for Controller Deployment in SDN

Hou Xiao-lan, W. Muqing
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引用次数: 1

Abstract

Software-defined networks(SDNs) can effectively solve the problem of scalability of current network system. The deployment of multi-controllers in the control plane is a very important task that can directly affect the network performance. In this paper, we research the controller deployment problem based on density clustering algorithm. The clustering by fast search and find of density peaks (CFSFDP) is a clustering algorithm by finding tall density peaks. In this paper, we put forward a controller deployment algorithm based on the CFSFDP algorithm in SDN to decrease propagation delay and communication consumption between switches and between switch and its controller. The delay density is calculated by introducing the k-nearest neighbors and the nearest neighbor with lower density. And the number of controllers is obtained automatically through the number of side lobes of $\gamma$ density curve by the kernel density estimation(KDE). Extensive simulations are conducted on Internet2 OS3E network topology. Compared to other methods, the results certify that our proposed algorithm has better performance considering communication consumption and propagation delay.
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一种有效的SDN控制器部署聚类算法
软件定义网络(sdn)可以有效解决当前网络系统的可扩展性问题。控制平面的多控制器部署是一项非常重要的任务,直接影响到网络的性能。本文研究了基于密度聚类算法的控制器部署问题。快速搜索发现密度峰聚类(CFSFDP)是一种寻找高密度峰的聚类算法。本文提出了一种基于SDN中CFSFDP算法的控制器部署算法,以降低交换机之间以及交换机与控制器之间的传播延迟和通信消耗。通过引入k近邻和密度较低的近邻来计算延迟密度。通过核密度估计(KDE),通过$\gamma$密度曲线的侧叶数自动获得控制器的个数。对internet2os3e网络拓扑结构进行了广泛的仿真。结果表明,在考虑通信消耗和传播延迟的情况下,该算法具有更好的性能。
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