Quality, Reliability, Security and Robustness in Heterogeneous Networks. 7th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2010, and Dedicated Short Range Communications Workshop, DSRC 2010, Houston, TX, USA, November 17-19, 2010, Revised Selected Papers

Research Article

Performance Analysis of Cloud Computing Centers

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  • @INPROCEEDINGS{10.1007/978-3-642-29222-4_18,
        author={Hamzeh Khazaei and Jelena Mišić and Vojislav Mišić},
        title={Performance Analysis of Cloud Computing Centers},
        proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Networks. 7th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2010, and Dedicated Short Range Communications Workshop, DSRC 2010, Houston, TX, USA, November 17-19, 2010, Revised Selected Papers},
        proceedings_a={QSHINE},
        year={2012},
        month={10},
        keywords={cloud computing performance analysis M/G/m queuing system response time},
        doi={10.1007/978-3-642-29222-4_18}
    }
    
  • Hamzeh Khazaei
    Jelena Mišić
    Vojislav Mišić
    Year: 2012
    Performance Analysis of Cloud Computing Centers
    QSHINE
    Springer
    DOI: 10.1007/978-3-642-29222-4_18
Hamzeh Khazaei1,*, Jelena Mišić2, Vojislav Mišić2
  • 1: University of Manitoba
  • 2: Ryerson University
*Contact email: hamzehk@cs.umanitoba.ca

Abstract

Cloud computing is a computing paradigm in which different computing resources, including infrastructure, hardware platforms, and software applications, are made accessible to remote users as services. Successful provision of infrastructure-as-a-service (IaaS) and, consequently, widespread adoption of cloud computing necessitates accurate performance evaluation that allows service providers to dimension their resources in order to fulfil the service level agreements with their customers. In this paper, we describe an analytical model for performance evaluation of cloud server farms, and demonstrate the manner in which important performance indicators such as request waiting time and server utilization may be assessed with sufficient accuracy.