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Economic Analysis of the SLA Mapping Approach for Cloud Computing Goods
Abstract
Because of the large number of different types of service level agreements (SLAs), computing resource markets face the challenge of low market liquidity. The authors therefore suggest restricting the number of different resource types to a small set of standardized computing resources to counteract this problem. Standardized computing resources are defined through SLA templates. SLA templates specify the structure of an SLA, the service attributes, the names of the service attributes, and the service attribute values. However, since existing approaches working with SLA templates are static so far, these approaches cannot reflect changes in user needs. To address this shortcoming, the chapter presents a novel approach to 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. Besides showing how public SLA templates are adapted to the demand of Cloud users, the chapter also analyzes 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 that has been adapted. In particular, it investigates how the costs differ with respect to the public SLA template adaptation method. The simulation results show that the use of heuristics for adaptation methods allows balancing the costs and benefits of the SLA mapping approach.
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