• DocumentCode
    2240176
  • Title

    The research of a resource-aware cloud computing architecture based on web security

  • Author

    Xiaoni Wang ; Xuedong Gao

  • Author_Institution
    Dongling Sch. of Econ. & Manage., Univ. of Sci. & Technol. Beijing, Beijing, China
  • fYear
    2012
  • fDate
    Oct. 30 2012-Nov. 1 2012
  • Firstpage
    440
  • Lastpage
    443
  • Abstract
    Web hosting has a lot of problems, such as low security, waste of bandwidth resource or sudden lack of resource. A self-adaptive cloud computing architecture - RA-Cloud architecture (Resource-aware Cloud Computing Architecture) based on web security in resource-aware situation is proposed. This architecture uses cloud computing technology and self-adaptive linear regression model to estimate the dynamic migration threshold and to search the most suitable neighbor node for data migration. This platform and algorithm distributes the huge amount of computing resource to many server “end” according to the resource constrained self-adaptive policy. The new method increases the user access speed, enhances the anti-attack ability, blocks the attacks effectively and improves the web site security.
  • Keywords
    Web sites; cloud computing; regression analysis; security of data; RA-cloud architecture; Web hosting; Web site security; antiattack ability; data migration; dynamic migration threshold estimation; neighbor node; resource constrained self-adaptive policy; resource-aware cloud computing architecture; resource-aware situation; self-adaptive cloud computing architecture; self-adaptive linear regression model; server end; Cloud computing; Computational modeling; Computer architecture; Linear regression; Security; Servers; Service-oriented architecture; Cloud computing architecture; Linear regression model; Resource-aware; Self-adaptive; Web security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4673-1855-6
  • Type

    conf

  • DOI
    10.1109/CCIS.2012.6664444
  • Filename
    6664444