• DocumentCode
    1759417
  • Title

    Decreasing Impact of SLA Violations:A Proactive Resource Allocation Approachfor Cloud Computing Environments

  • Author

    Morshedlou, Hossein ; Meybodi, Mohammad Reza

  • Author_Institution
    Dept. of Comput. Eng. & Inf. Sci., AmirKabir Univ. of Technol., Tehran, Iran
  • Volume
    2
  • Issue
    2
  • fYear
    2014
  • fDate
    April-June 2014
  • Firstpage
    156
  • Lastpage
    167
  • Abstract
    User satisfaction as a significant antecedent to user loyalty has been highlighted by many researchers in market based literatures. SLA violation as an important factor can decrease users´ satisfaction level. The amount of this decrease depends on user´s characteristics. Some of these characteristics are related to QoS requirements and announced to service provider through SLAs. But some of them are unknown for service provider and selfish users are not interested to reveal them truly. Most the works in literature ignore considering such characteristics and treat users just based on SLA parameters. So, two users with different characteristics but similar SLAs have equal importance for the service provider. In this paper, we use two user´s hidden characteristics, named willingness to pay for service and willingness to pay for certainty, to present a new proactive resource allocation approach with aim of decreasing impact of SLA violations. New methods based on learning automaton for estimation of these characteristics are provided as well. To validate our approach we conducted some numerical simulations in critical situations. The results confirm that our approach has ability to improve users´ satisfaction level that cause to gain in profitability.
  • Keywords
    cloud computing; contracts; resource allocation; QoS requirements; SLA violations; cloud computing environment; proactive resource allocation approach; profitability; quality of service; service level agreements; service provider; user characteristics; user satisfaction; Cloud computing; Decision making; Learning automata; Market research; Profitability; Quality of service; Resource management; Users satisfaction level; cloud service; learning automaton; resource allocation; willingness to pay;
  • fLanguage
    English
  • Journal_Title
    Cloud Computing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    2168-7161
  • Type

    jour

  • DOI
    10.1109/TCC.2014.2305151
  • Filename
    6734676