A Multi-model Optimization Framework for the Model Driven Design of Cloud Applications

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• 作者：Danilo Ardagna (17)
  Giovanni Paolo Gibilisco (17)
  Michele Ciavotta (17)
  Alexander Lavrentev (17)
  
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8636
• 期：1
• 页码：61-76
• 全文大小：390 KB
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• 作者单位：Danilo Ardagna (17)
  Giovanni Paolo Gibilisco (17)
  Michele Ciavotta (17)
  Alexander Lavrentev (17)
  
  17. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milano, Italy
  
• ISSN：1611-3349

文摘

The rise and adoption of the Cloud computing paradigm had a strong impact on the ICT world in the last few years; this technology has now reached maturity and Cloud providers offer a variety of solutions and services to their customers. However, beside the advantages, Cloud computing introduced new issues and challenges. In particular, the heterogeneity of the Cloud services offered and their relative pricing models makes the identification of a deployment solution that minimizes costs and guarantees QoS very complex. Performance assessment of Cloud based application needs for new models and tools to take into consideration the dynamism and multi-tenancy intrinsic of the Cloud environment. The aim of this work is to provide a novel mixed integer linear program (MILP) approach to find a minimum cost feasible cloud configuration for a given cloud based application. The feasibility of the solution is considered with respect to some non-functional requirements that are analyzed through multiple performance models with different levels of accuracy. The initial solution is further improved by a local search based procedure. The quality of the initial feasible solution is compared against first principle heuristics currently adopted by practitioners and Cloud providers.