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Flow-level traffic matrix generation for various data center networks

机译:各种数据中心网络的流级流量矩阵生成

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摘要

The number of data centers deployed by governments, enterprises, and universities has been increased affected by the development of cloud computing technologies to reduce CAPAX and OPEX. Many architectures or topologies for data center networks have been proposed to address the diverse purposes and requirements. However, the construction of data centers incurs significant costs. Moreover, there are many technologies that can affect the structure of the data center. Before building a data center, it must be confirmed that it possesses the characteristics necessary to satisfy requirements. Efficient ways to find and confirm network characteristics include simulation and tests using a traffic generation method. Our proposed method is designed to generate network traffic that address many characteristics of data center networks explored by several studies. The proposed method generates network traffic utilizing flow-level traffic matrix, not directly generates packets. We used Python programming language to create traffic matrix and iPerf to generate network packets. To evaluate it, we compared the generation results to real network traffic collected from a data center network. The result shows that the generated traffic is similar with the real network traffic.
机译:受云计算技术发展以减少CAPAX和OPEX的影响,政府,企业和大学部署的数据中心数量已增加。已经提出了用于数据中心网络的许多架构或拓扑,以解决各种目的和要求。但是,数据中心的建设会产生大量成本。此外,有许多技术可以影响数据中心的结构。在建立数据中心之前,必须确认它具有满足要求所必需的特性。查找和确认网络特征的有效方法包括使用流量生成方法进行仿真和测试。我们提出的方法旨在生成可解决数项研究探索的数据中心网络许多特征的网络流量。所提出的方法利用流级流量矩阵来生成网络流量,而不是直接生成数据包。我们使用Python编程语言创建流量矩阵,并使用iPerf生成网络数据包。为了对其进行评估,我们将生成结果与从数据中心网络收集的实际网络流量进行了比较。结果表明,生成的流量与实际的网络流量相似。

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