数据中心集群流量预测

2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T) Pub Date : 2020-10-06 DOI:10.1109/PICST51311.2020.9468006

Andriy Kovalenko, Heorhii Kuchuk, Viacheslav Radchenko, A. Poroshenko

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引用次数: 1

摘要

提出了一种数据中心集群流量预测方法。这种预测是基于交通概率密度函数的构造。该方法利用了分布函数连续主要导致的样本量的扩大，对于小样本，给出了比现有方法更准确、更稳定的评价。该方法对具有长期脉动和长期依赖的流量分析更为有效。

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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Predicting of Data Center Cluster Traffic

The paper proposes a method for predicting of Data Center cluster traffic. Such prediction is based on the construction of the traffic probability density function. The method uses the expansion of the sample size due to the continuous majorant of the distribution function and, for small samples, gives a more accurate and stable evaluation than the existing methods. The method is more effective in analyzing a traffic with long-term pulsations, as well as long-term dependent traffic.

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来源期刊

2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T)

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