QoS-driven Service Selection Methods for Cost Minimization of Composite Cloud Services under Stochastic Runtime Performance
| Autor: | Mu-Jung Tsai, 蔡沐容 |
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| Rok vydání: | 2014 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 102 Cloud computing has become the most promising next-generation computing platform recently. Composite cloud services based on the methodologies of Software as a Service (SaaS ) and Service-Oriented Architecture (SOA) are transforming how people develop and use software and expected to bring a lot of benefits for both software developers and users. Cloud service providers have to deal with the issues of service selection when composing a composite cloud service, which can be viewed as a constrained optimization problem aiming to minimize the total costs of providing such services with respect to the constraints of Service Level Agreement (SLA). The service selection problem becomes even more challenging when considering the stochastic QoS performance. This thesis presents two approaches to the service selection problem in dynamic cloud environments where services’ performance might varies with time. The first one is an iterative compound approach, with each iteration containing three steps: Integer Linear Programming (ILP) optimization, simulation of stochastic performance, and adaptation. The second approach is a one-step method based on the Chebyshev’s theorem and nonlinear programming. It takes into consideration the stochastic performance in the objective function of a nonlinear programming formulation. We have conducted a series of simulation experiments to evaluate the proposed approaches. Our approaches outperform the previous method in the literature significantly in terms of total cost reduction. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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