Cost and Benefit of the SLA Mapping Approach for Defining Standardized Goods in Cloud Computing Markets
AbstractDue to the large variety in computing resources and, consequently, the large number of different types of Service Level Agreements (SLAs), any market for computing resources faces the potential problem of a low market liquidity. To counteract this problem, offering a set of standardized computing resources is appropriate. Each of these standardized computing resources is defined through an SLA template. An SLA template defines the structure of an SLA, the attributes, the names of the attributes, and the attribute values. Since these SLA templates are currently static, they cannot reflect changes in users' needs. To address this shortcoming, we present the novel approach of adaptive SLA matching. This approach adapts SLA templates based on SLA mappings by allowing Cloud users to define mappings between public SLA templates, which are 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 adapt to the demand of users, we also analyze the benefits and costs 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, within this paper, we investigate the cost depending on the use of different public SLA template adaptation methods. The simulation results show that the use of heuristics within adaptation methods helps balancing the cost and benefit of the SLA mapping approach.
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Bibliographic InfoPaper provided by Seoul National University; Technology Management, Economics, and Policy Program (TEMEP) in its series TEMEP Discussion Papers with number 201069.
Length: 8 pages
Date of creation: Dec 2010
Date of revision: Dec 2010
Publication status: Published in UCC 2010, International Conference on Utility and Cloud Computing, Chennai, India, December 2010.
Cloud economics; computing markets; market liquidity; simulation.;
Find related papers by 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 and Pricing - - - General
- D45 - Microeconomics - - Market Structure and Pricing - - - 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
- M15 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - IT Management
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- Ivan Breskovic & Michael Maurer & Vincent C. Emeakaroha & Ivona Brandic & Jorn Altmann, 2011. "Towards Autonomic Market Management in Cloud Computing Infrastructures," TEMEP Discussion Papers 201174, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Apr 2011.
- Ivan Breskovic & Michael Maurer & Vincent C. Emeakaroha & Ivona Brandic & Jorn Altmann, 2011. "Achieving Market Liquidity through Autonomic Cloud Market Management," TEMEP Discussion Papers 201180, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Aug 2011.
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