Performance Evaluation of a Cloud Datacenter Using CPU Utilization Data

Chen Li (), Junjun Zheng, Hiroyuki Okamura and Tadashi Dohi
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Chen Li: Department of Computer Science and Systems Engineering, Kyushu Institute of Technology, Iizuka 8208502, Japan
Junjun Zheng: Graduate School of Information Science and Technology, Osaka University, Osaka 5650871, Japan
Hiroyuki Okamura: Graduate School of Advanced Science Engineering, Hiroshima University, Higashihiroshima 7398527, Japan
Tadashi Dohi: Graduate School of Advanced Science Engineering, Hiroshima University, Higashihiroshima 7398527, Japan

Mathematics, 2023, vol. 11, issue 3, 1-16

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.

Keywords: performance evaluation; CPU utilization; non-homogeneous Poisson process (NHPP) (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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