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A SIMULATION AND EMULATION STUDY OF SDN-BASED MULTIPATH ROUTING FOR FAT-TREE DATA CENTER NETWORKS

机译:基于SDN的FAT-树数据中心网络多路径路由仿真研究

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The fat tree topology with multipath capability has been used in many recent data center networks (DCNs) for increased bandwidth and fault tolerance. Traditional routing protocols have only limited support for multipath routing, and cannot fully utilize the available bandwidth in such networks. In this paper, we study multipath routing for fat tree networks. We formulate the problem as a linear program and prove its NP-completeness. We propose a practical solution, which takes advantage of the emerging software-defined networking paradigm. Our algorithm relies on a central controller to collect necessary network state information in order to make optimized routing decisions. We implemented the algorithm as an OpenFlow controller module and validated it with Mininet emulation. We also developed a fluid-based DCN simulator and conducted experiments, which show that our algorithm outperforms the traditional multipath algorithm based on random assignments, both in terms of increased throughput and in reduced end-to-end delay.
机译:具有多路径功能的胖树拓扑已在许多最近的数据中心网络(DCN)中使用,以增加带宽和容错能力。传统的路由协议仅对多路径路由提供有限的支持,而不能充分利用此类网络中的可用带宽。在本文中,我们研究了胖树网络的多路径路由。我们将问题表示为线性程序,并证明其NP完备性。我们提出了一种实用的解决方案,该方案利用了新兴的软件定义网络范例。我们的算法依靠中央控制器来收集必要的网络状态信息,以便做出优化的路由决策。我们将该算法实现为OpenFlow控制器模块,并通过Mininet仿真对其进行了验证。我们还开发了基于流体的DCN模拟器并进行了实验,结果表明,在增加吞吐量和减少端到端延迟方面,我们的算法均优于基于随机分配的传统多路径算法。

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