Predicting of Data Center Cluster Traffic

Autor:	Viacheslav Radchenko, Heorhii Kuchuk, Andriy Kovalenko, Anton Poroshenko
Rok vydání:	2020
Předmět:	Distribution function Fractal Sample size determination Computer science business.industry Computer Science::Networking and Internet Architecture Cluster (physics) Probability density function Data center Statistical physics business
Zdroj:	2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T).
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6ca3d5c327bce4e38b7f729d839e4733 https://doi.org/10.1109/picst51311.2020.9468006 Zobrazit plný text záznamu