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Performance Evaluation of a Cloud Datacenter Using CPU Utilization Data

Authors :
Chen Li
Junjun Zheng
Hiroyuki Okamura
Tadashi Dohi
Source :
Mathematics, Vol 11, Iss 3, p 513 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Cloud computing and its associated virtualization have already been the most vital architectures in the current computer system design. Due to the popularity and progress of cloud computing in different organizations, performance evaluation of cloud computing is particularly significant, which helps computer designers make plans for the system’s capacity. This paper aims to evaluate the performance of a cloud datacenter Bitbrains, using a queueing model only from CPU utilization data. More precisely, a simple but non-trivial queueing model is used to represent the task processing of each virtual machine (VM) in the cloud, where the input stream is supposed to follow a non-homogeneous Poisson process (NHPP). Then, the parameters of arrival streams for each VM in the cloud are estimated. Furthermore, the superposition of estimated arrivals is applied to represent the CPU behavior of an integrated virtual platform. Finally, the performance of the integrated virtual platform is evaluated based on the superposition of the estimations.

Details

Language :
English
ISSN :
22277390
Volume :
11
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Mathematics
Publication Type :
Academic Journal
Accession number :
edsdoj.4e0c6cb2b2124df4b997490898edb52e
Document Type :
article
Full Text :
https://doi.org/10.3390/math11030513