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A method for enhancing end-to-end transfer efficiency via performance tuning factors on dedicated circuit networks with a public cloud platform

机译:一种通过具有公共云平台的专用电路网络上的性能调整因子来提高端到端传输效率的方法

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摘要

There has been a great deal of recent research interest regarding the storage and utilization of big data via remote cloud platforms. The efficiency of large data transfers from remote cloud platforms is a critical issue, and dedicated networks are used for data transfer. To resolve the data transfer efficiency issue, it is necessary to tune the L2-related performance items in the transport equipment and to regulate performance factors, such as window size, between IP layer servers, during the configuration of an end-to-end research network. It is also necessary to tune factor values related to performance items in transport equipment. System level kernel parameter tuning is also needed and results in improved throughput. Here, we measure throughput according to L2-related tuning factors and IP levels, including kernel parameter turning, and present an analysis of the measurement results. The experimental results show that end-to-end servers with tuned factors, in addition to system level kernel parameter tuning, can effectively utilize the available bandwidth.
机译:关于通过远程云平台存储和利用大数据的最新研究兴趣很大。从远程云平台进行大数据传输的效率是一个关键问题,并且专用网络用于数据传输。为了解决数据传输效率问题,在端到端研究的配置过程中,有必要调整传输设备中与L2相关的性能项目,并调节IP层服务器之间的性能因素,例如窗口大小。网络。还需要调整与运输设备中性能项目相关的因子值。还需要系统级内核参数调整,从而提高吞吐量。在这里,我们根据L2相关的调整因子和IP级别(包括内核参数转换)来测量吞吐量,并给出对测量结果的分析。实验结果表明,具有调整因子的端到端服务器,除了系统级内核参数调整之外,还可以有效利用可用带宽。

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