• DocumentCode
    3125578
  • Title

    An Economic Model for Self-Tuned Cloud Caching

  • Author

    Dash, Debabrata ; Kantere, Verena ; Ailamaki, Anastasia

  • Author_Institution
    Carnegie Mellon Univ., Pittsburgh, PA
  • fYear
    2009
  • fDate
    March 29 2009-April 2 2009
  • Firstpage
    1687
  • Lastpage
    1693
  • Abstract
    Cloud computing, the new trend for service infrastructures requires user multi-tenancy as well as minimal capital expenditure. In a cloud that services large amounts of data that are massively collected and queried, such as scientific data, users typically pay for query services. The cloud supports caching of data in order to provide quality query services. User payments cover query execution costs and maintenance of cloud infrastructure, and incur cloud profit. The challenge resides in providing efficient and resource-economic query services while maintaining a profitable cloud. In this work we propose an economic model for self-tuned cloud caching targeting the service of scientific data. The proposed economy is adapted to policies that encourage high-quality individual and overall query services but also brace the profit of the cloud. We propose a cost model that takes into account all possible query and infrastructure expenditure. The experimental study proves that the proposed solution is viable for a variety of workloads and data.
  • Keywords
    Internet; cache storage; costing; economics; information services; profitability; query processing; cloud computing; cloud infrastructure; cloud profit; data caching; economic model; minimal capital expenditure; profitable cloud; quality query service; query execution cost; query execution maintenance; resource-economic query service; self-tuned cloud caching; service infrastructure; user multitenancy; user payment; Bandwidth; Cloud computing; Computer network management; Costs; Data engineering; Databases; Environmental economics; Space technology; Web and internet services; Web server; cache; cloud economy; self-tuning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering, 2009. ICDE '09. IEEE 25th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    1084-4627
  • Print_ISBN
    978-1-4244-3422-0
  • Electronic_ISBN
    1084-4627
  • Type

    conf

  • DOI
    10.1109/ICDE.2009.143
  • Filename
    4812593