Performance Evaluation of a Cloud Datacenter Using CPU Utilization Data

被引:2
|
作者
Li, Chen [1 ]
Zheng, Junjun [2 ]
Okamura, Hiroyuki [3 ]
Dohi, Tadashi [3 ]
机构
[1] Kyushu Inst Technol, Dept Comp Sci & Syst Engn, Iizuka 8208502, Japan
[2] Osaka Univ, Grad Sch Informat Sci & Technol, Osaka 5650871, Japan
[3] Hiroshima Univ, Grad Sch Adv Sci Engn, Higashihiroshima 7398527, Japan
关键词
performance evaluation; CPU utilization; non-homogeneous Poisson process (NHPP); MAXIMUM-LIKELIHOOD-ESTIMATION; QUEUING-SYSTEMS; QUEUES;
D O I
10.3390/math11030513
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] On-line performance evaluation of RAID 5 using CPU utilization
    Jin, H
    Yang, HN
    Zhang, JL
    SIGNAL AND DATA PROCESSING OF SMALL TARGETS 1998, 1998, 3373 : 498 - 509
  • [2] CPU Utilization in a Multitenant Cloud
    Velkoski, Goran
    Simjanoska, Monika
    Ristov, Sasko
    Gusev, Marjan
    2013 IEEE EUROCON, 2013, : 242 - 249
  • [3] Using Branch-and-Price to maximize redundant network utilization in cloud datacenter
    Wang, Shuo
    Wang, Qiqi
    Zhang, Hongjie
    Li, Jing
    PROCEEDINGS OF 2017 3RD INTERNATIONAL CONFERENCE OF CLOUD COMPUTING TECHNOLOGIES AND APPLICATIONS (CLOUDTECH), 2017, : 96 - 103
  • [4] A Study of the Performance of a Cloud Datacenter Server
    Mershad, Khaleel
    Artail, Hassan
    Saghir, Mazen A. R.
    Hajj, Hazem
    Awad, Mariette
    IEEE TRANSACTIONS ON CLOUD COMPUTING, 2017, 5 (04) : 590 - 603
  • [5] A mathematical model to analyze the utilization of a cloud datacenter middleware
    Mershad, Khaleel
    Artail, Hassan
    Saghir, Mazen
    Hajj, Hazem
    Awad, Mariette
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2016, 59 : 399 - 415
  • [6] Predicting host CPU utilization in the cloud using evolutionary neural networks
    Mason, Karl
    Duggan, Martin
    Barrett, Enda
    Duggan, Jim
    Howley, Enda
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 86 : 162 - 173
  • [7] Predicting Host CPU Utilization in Cloud Computing using Recurrent Neural Networks
    Duggan, Martin
    Mason, Karl
    Duggan, Jim
    Howley, Enda
    Barrett, Enda
    2017 12TH INTERNATIONAL CONFERENCE FOR INTERNET TECHNOLOGY AND SECURED TRANSACTIONS (ICITST), 2017, : 67 - 72
  • [8] Efficient Datacenter Resource Utilization Through Cloud Resource Overcommitment
    Dabbagh, Mehiar
    Hamdaoui, Bechir
    Guizani, Mohsen
    Rayes, Ammar
    2015 IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), 2015, : 330 - 335
  • [9] Boosted regression for predicting CPU utilization in the cloud with periodicity
    Quoc, Khanh Nguyen
    Tong, Van
    Dao, Cuong
    Le, Tuyen Ngoc
    Tran, Duc
    JOURNAL OF SUPERCOMPUTING, 2024, 80 (18): : 26036 - 26060
  • [10] Performance Evaluation of Data Intensive Computing In the Cloud
    Ahuja, Sanjay P.
    Kaza, Bhagavathi
    INTERNATIONAL JOURNAL OF CLOUD APPLICATIONS AND COMPUTING, 2014, 4 (02) : 34 - 47