• DocumentCode
    654197
  • Title

    Quality Assessment of Software as a Service on Cloud Using Fuzzy Logic

  • Author

    Baliyan, Niyati ; Kumar, Sudhakar

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Indian Inst. of Technol. Roorkee, Roorkee, India
  • fYear
    2013
  • fDate
    16-18 Oct. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Cloud computing is a business model which provides on demand services on the pay-per-use premise. Software as a Service (SaaS) is one of the delivery models for cloud computing, where software ownership by the SaaS provider is isolated from its use by the SaaS customer. The notion of quality is central to any service provision. Also, it is important to evaluate the quality of SaaS in order to be able to improve it. Traditional software engineering quality models are not effusively suitable for this purpose due to difference in the nature of software and service. In the past, a few approaches to service quality estimation have been proposed. Some of these approaches extend quality characteristics from existing quality models and even devise SaaS quality metrics, while others discuss quality around Service Level Agreement (SLA) and Quality of Service (QoS) parameters. In this paper, some representative quality factors have been identified by analyzing literature and a model based on fuzzy logic has been proposed to assess SaaS quality. Such a model of quality criteria may provide a ground for more comprehensive quality model which may assist a SaaS customer to choose a higher quality service from available services on cloud; the quality model may also serve as a guideline to SaaS provider to improve the quality of service provided.
  • Keywords
    cloud computing; contracts; fuzzy logic; quality of service; software quality; QoS parameters; SLA parameters; SaaS customer; SaaS provider; SaaS quality evaluation; SaaS quality metrics; business model; cloud computing; delivery models; fuzzy logic; on demand services; quality of service parameters; service level agreement parameters; service quality estimation; software as a service quality assessment; software engineering quality models; software ownership; Adaptation models; Cloud computing; Computational modeling; Estimation; Fuzzy logic; Software as a service;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing in Emerging Markets (CCEM), 2013 IEEE International Conference on
  • Conference_Location
    Bangalore
  • Print_ISBN
    978-1-4799-0027-5
  • Type

    conf

  • DOI
    10.1109/CCEM.2013.6684439
  • Filename
    6684439