Translation from UML to Markov Model: A Performance modeling Framework for Managing Behavior of Multiple Collaborative Sessions and Instances

摘要

Performance evaluation of distributed system is always an intricate undertaking where system behavior is normally distributed among several components those are physically distributed. Bearing this concept in mind, we delineate a performance modeling framework for a distributed system that proposes a translation process from high level UML notation to Markov model and solves the model for relevant performance metrics. To capture the system dynamics through our proposed framework we outline a specification style that focuses on UML collaboration and activity as reusable specification building blocks. To present the UML specification style we focus on how to coordinate explicitly multiple collaborative sessions occurring at the same time. Design alternatives of system architecture are considered. to generate the performance model to show how these design alternatives thus affect the system performance under different work load. The proposed performance modeling framework provides prediction result of a system such as mean response time and resource utilization. The applicability of our proposed framework is demonstrated in the context of performance modeling of a distributed system.