Architecture-based runtime software evolution
Proceedings of the 20th international conference on Software engineering
The Vision of Autonomic Computing
Computer
Model-Based Performance Prediction in Software Development: A Survey
IEEE Transactions on Software Engineering
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
Microreboot — A technique for cheap recovery
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
The Future of Software Performance Engineering
FOSE '07 2007 Future of Software Engineering
Self-Managed Systems: an Architectural Challenge
FOSE '07 2007 Future of Software Engineering
Implementing Adaptive Performance Management in Server Applications
SEAMS '07 Proceedings of the 2007 International Workshop on Software Engineering for Adaptive and Self-Managing Systems
EUROMICRO '07 Proceedings of the 33rd EUROMICRO Conference on Software Engineering and Advanced Applications
The Palladio component model for model-driven performance prediction
Journal of Systems and Software
Increasing system dependability through architecture-based self-repair
Architecting dependable systems
Model-based self-adaptive resource allocation in virtualized environments
Proceedings of the 6th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
Reverse engineering of dependency graphs via dynamic analysis
Proceedings of the 5th European Conference on Software Architecture: Companion Volume
Performance simulation of runtime reconfigurable component-based software architectures
ECSA'11 Proceedings of the 5th European conference on Software architecture
Hi-index | 0.00 |
This paper gives an overview about our current work on a framework which aims at operating component-based software systems more efficiently. Efficiency, in terms of the number of allocated data center resources, is improved by executing architecture-level runtime adaptations based on current workload situations. The proposed framework, called SLAstic, is described and open questions to be answered in future work are raised.