• DocumentCode
    172946
  • Title

    Non-intrusive Critical System Event Recognition and Prediction in Cloud

  • Author

    Yuanyao Liu ; Zhengping Wu

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Bridgeport, Bridgeport, CT, USA
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    659
  • Lastpage
    666
  • Abstract
    The cloud computing platform provides an efficient and flexible way to offer services and computation facilities to users. However, reliability in the cloud is an important factor to measure the performance of a virtualized cloud computing platform. System failure, software failure, outside attacks, and mis-actions of virtual machines make the cloud computing platform unstable and unreliable. In order to avoid critical events affect reliability, resources, applications, and services can be scheduled around predicted failure and limit the impact. In the cloud computing platform, different virtual machines may generate number of system events. Events from different virtual machines can affect system stability together. Such mechanisms are especially important for cloud computing environment. In this paper, we propose a framework to recognize and predict system critical events that come from different virtual machines to increase system stability of cloud computing environment.
  • Keywords
    cloud computing; software reliability; virtual machines; virtualisation; cloud computing environment; computation facilities; nonintrusive critical system event prediction; nonintrusive critical system event recognition; outside attacks; software failure; system failure; system stability; virtual machines; virtualized cloud computing platform; Cloud computing; Indexes; Knowledge based systems; Pattern recognition; Reliability; Virtual machining; Cloud Computing; Event Prediction; Event Recognition; Virtualizations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing (CLOUD), 2014 IEEE 7th International Conference on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5062-1
  • Type

    conf

  • DOI
    10.1109/CLOUD.2014.93
  • Filename
    6973799