A Software Performance Engineering Tool based on the UML-SPT
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
A Framework for Simulation Models of Service-Oriented Architectures
SIPEW '08 Proceedings of the SPEC international workshop on Performance Evaluation: Metrics, Models and Benchmarks
The Palladio component model for model-driven performance prediction
Journal of Systems and Software
QoSA '08 Proceedings of the 4th International Conference on Quality of Software-Architectures: Models and Architectures
Self-adaptive software: Landscape and research challenges
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
An adaptation framework enabling resource-efficient operation of software systems
Proceedings of the Warm Up Workshop for ACM/IEEE ICSE 2010
JMT: performance engineering tools for system modeling
ACM SIGMETRICS Performance Evaluation Review
Service Oriented Computing and Applications
Hi-index | 0.00 |
Architectural runtime reconfiguration is a promising means for controlling the quality of service (QoS) of distributed software systems. Particularly self-adaptation approaches rely on runtime reconfiguration capabilities provided by the systems under control. For example, our online capacity management approach SLAstic employs changing component deployments and server allocations to control the performance and resource efficiency of component-based (C-B) software systems at runtime. In this context, we developed a performance simulator for runtime configurable C-B software systems, called SLAstic.SIM. The system architectures to be simulated are specified as instances of the Palladio Component Model (PCM). The simulation is driven by external workload traces and reconfiguration plans which can be requested during simulation, based on continuously accessible monitoring data of the simulated systems. This paper demonstrates SLAstic.SIM including a quantitative evaluation of its performance.