Modeling parameter and context dependencies in online architecture-level performance models
Fabian Brosig, Nikolaus Huber, Samuel Kounev · 2012
Modern service-oriented enterprise systems have increasingly complex and dynamic loosely-coupled architectures that often exhibit poor performance and resource efficiency and have high operating costs. This is due to the inability to predict at run-time the effect of dynamic changes in the system environment and adapt the system configuration accordingly. Architecture-level performance models provide a powerful tool for performance prediction, however, current approaches to modeling the execution context of software components are not suitable for use at run-time. In this paper, we analyze the typical online performance prediction scenarios and propose a novel performance meta-model for expressing and resolving parameter and context dependencies, specifically designed for use in online scenarios. We motivate and validate our approach in the context of a realistic and representative online performance prediction scenario based on the SPECjEnterprise2010 standard benchmark.