• DocumentCode
    2786161
  • Title

    Remediating Overload in Over-Subscribed Computing Environments

  • Author

    Wang, Long ; Hosn, Rafah A. ; Tang, Chunqiang

  • Author_Institution
    Thomas J. Watson Res. Center, IBM Corp., Hawthorne, NY, USA
  • fYear
    2012
  • fDate
    24-29 June 2012
  • Firstpage
    860
  • Lastpage
    867
  • Abstract
    Resource over subscription brings the risk of resource overload. This paper proposes a mechanism to remediate overload without assuming there is always resource available for migration. A work value notion is introduced to compare importance of VMs, and the overload remediation problem is formulated as a variant of Removable Online Multi-Knapsack Problem. An algorithm is proposed to solve this optimization problem. The mechanism is implemented in a large commercial Cloud environment. Experiments and model-based studies demonstrate the effectiveness of the proposed mechanism in remediating overload and its performance in maximizing work values provided by computing environments (27% higher work values than the baseline algorithm in our study).
  • Keywords
    cloud computing; knapsack problems; optimisation; performance evaluation; resource allocation; virtual machines; baseline algorithm; commercial cloud environment; model-based studies; optimization problem; overload remediation problem; oversubscribed computing environments; removable online multiknapsack problem; resource migration; resource overloading risk; resource oversubscription; work value maximization; work value notion; Complexity theory; Computational modeling; Memory management; Monitoring; Servers; Throughput; Virtual machine monitors; VM placement; optimization; over-commitment; over-subscription; overload; quiesce;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    2159-6182
  • Print_ISBN
    978-1-4673-2892-0
  • Type

    conf

  • DOI
    10.1109/CLOUD.2012.53
  • Filename
    6253589