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Cost–Benefit Analysis of an SLA Mapping Approach for Defining Standardized Cloud Computing Goods

Author

Listed:
  • Michael Maurera

    () (Vienna University of Technology)

  • Vincent C. Emeakarohaa

    () (Vienna University of Technology)

  • Ivona Brandica

    () (Vienna University of Technology)

  • Jorn Altmann

    () (College of Engineering, Seoul National University)

Abstract

Due to the large variety in computing resources and, consequently, the large number of different types of service level agreements (SLAs), computing resource markets face the problem of a low market liquidity. Restricting the number of different resource types to a small set of standardized computing resources seems to be the appropriate solution to counteract this problem. Standardized computing resources are defined through an SLA template. An SLA template defines the structure of an SLA, the service attributes, the names of the service attributes, and the service attribute values. However, since existing research results have only introduced static SLA templates so far, the SLA templates cannot reflect changes in user needs and market structures. To address this shortcoming, we present a novel approach of adaptive SLA matching. This approach adapts SLA templates based on SLA mappings of users. It allows Cloud users to define mappings between a public SLA template, which is available in the Cloud market, and their private SLA templates, which are used for various in-house business processes of the Cloud user. Besides showing how public SLA templates are adapted to the demand of Cloud users, we also analyze the costs and benefits of this approach. Costs are incurred every time a user has to define a new SLA mapping to a public SLA template due to its adaptation. In particular, we investigate how the costs differ with respect to the public SLA template adaptation method. The simulation results show that the use of heuristics within adaptation methods allows balancing the costs and benefits of the SLA mapping approach.

Suggested Citation

  • Michael Maurera & Vincent C. Emeakarohaa & Ivona Brandica & Jorn Altmann, 2011. "Cost–Benefit Analysis of an SLA Mapping Approach for Defining Standardized Cloud Computing Goods," TEMEP Discussion Papers 201177, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jul 2011.
  • Handle: RePEc:snv:dp2009:201177
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    File URL: ftp://147.46.237.98/DP-77.pdf
    File Function: First version, 2011
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    References listed on IDEAS

    as
    1. Marcel Risch & Jorn Altmann, 2009. "Enabling Open Cloud Markets Through WS-Agreement Extensions," TEMEP Discussion Papers 200920, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Oct 2009.
    2. Marcel Risch & Jorn Altmann & Li Guo & Alan Fleming & Costas Courcoubetis, 2010. "The GridEcon Platform: A Business Scenario Testbed for Commercial Cloud Services," TEMEP Discussion Papers 201039, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jan 2010.
    3. Marcel Risch & Ivona Brandic & Jorn Altmann, 2009. "Using SLA Mapping to Increase Market Liquidity," TEMEP Discussion Papers 200937, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Oct 2009.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Ivan Breskovic & Ivona Brandic & Jorn Altmann, 2013. "Maximizing Liquidity in Cloud Markets through Standardization of Computational Resources," TEMEP Discussion Papers 2013100, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Feb 2013.
    2. Ivan Breskovic & Jorn Altmann & Ivona Brandic, 2012. "Creating Standardized Products for Electronic Markets," TEMEP Discussion Papers 201296, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Sep 2012.

    More about this item

    Keywords

    Service level agreements; Cloud architecture; Cloud markets; market liquidity; cost modeling; utility modeling; SLA matching; goods standardization.;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • D45 - Microeconomics - - Market Structure, Pricing, and Design - - - Rationing; Licensing
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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