• DocumentCode
    3140675
  • Title

    A Pattern-Based Approach to Cloud Transformation

  • Author

    Chee, Yi-Min ; Zhou, Nianjun ; Meng, Fan Jing ; Bagheri, Saeed ; Zhong, Peide

  • Author_Institution
    T.J. Watson Res. Center, IBM, Hawthorne, NY, USA
  • fYear
    2011
  • fDate
    4-9 July 2011
  • Firstpage
    388
  • Lastpage
    395
  • Abstract
    With the growing interest in cloud computing, more and more businesses are looking not only to migrate their applications to the cloud but also to transform them to better leverage capabilities that are provided by cloud platforms or to enable new business models that are facilitated by the cloud. One problem clients face in this area is a lack of experience and knowledge as to how best to accomplish this transformation. We propose a Cloud Transformation Advisor (CTA) which helps users to select appropriate enablement patterns from a knowledge base of best practices when performing transformation planning. This knowledge base uses a structured representation to capture application information, cloud platform capability information, and enablement pattern information in order to facilitate pattern selection. We describe this representation and a mathematical model which leverages it to choose the "best" combination of patterns for a given transformation problem. We present an example which illustrates the approach, and describe the usage of the CTA.
  • Keywords
    cloud computing; knowledge based systems; planning (artificial intelligence); CTA; application information; business models; cloud computing; cloud platform capability information; cloud transformation advisor; enablement pattern information; knowledge base; mathematical model; pattern selection; pattern-based approach; transformation planning; Best practices; Cloud computing; Context; Knowledge based systems; Pattern matching; Transforms; advisor; cloud computing; patterns; transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing (CLOUD), 2011 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    2159-6182
  • Print_ISBN
    978-1-4577-0836-7
  • Electronic_ISBN
    2159-6182
  • Type

    conf

  • DOI
    10.1109/CLOUD.2011.86
  • Filename
    6008734