%0 Conference Paper %1 KoBrHuRe2010-SCC-Towards %A Kounev, Samuel %A Brosig, Fabian %A Huber, Nikolaus %A Reussner, Ralf %B Proceedings of the 7th IEEE International Conference on Services Computing (SCC 2010), July 5-10, Miami, Florida, USA %D 2010 %I IEEE Computer Society %K Application_quality_of_service_management Automated_model_learning Design_of_software_and_systems Formal_architecture_modeling Online_monitoring_and_forecasting Performance Prediction Resource_management SOA Self-adaptive-systems Self-aware-computing descartes t_visionposition %T Towards self-aware performance and resource management in modern service-oriented systems %X Modern service-oriented systems have increasingly complex 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 (e.g., varying service workloads) and adapt the system configuration accordingly. In this paper, we describe a long-term vision and approach for designing systems with built-in self-aware performance and resource management capabilities. We advocate the use of architecture-level performance models extracted dynamically from the evolving system configuration and maintained automatically during operation. The models will be exploited at run-time to adapt the system to changes in the environment ensuring that resources are utilized efficiently and performance requirements are continuously satisfied.

@inproceedings{KoBrHuRe2010-SCC-Towards, abstract = {Modern service-oriented systems have increasingly complex 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 (e.g., varying service workloads) and adapt the system configuration accordingly. In this paper, we describe a long-term vision and approach for designing systems with built-in self-aware performance and resource management capabilities. We advocate the use of architecture-level performance models extracted dynamically from the evolving system configuration and maintained automatically during operation. The models will be exploited at run-time to adapt the system to changes in the environment ensuring that resources are utilized efficiently and performance requirements are continuously satisfied.}, added-at = {2020-04-06T11:20:59.000+0200}, author = {Kounev, Samuel and Brosig, Fabian and Huber, Nikolaus and Reussner, Ralf}, biburl = {https://www.bibsonomy.org/bibtex/248b5197300e91f98e34800007f258178/se-group}, booktitle = {Proceedings of the 7th IEEE International Conference on Services Computing (SCC 2010), July 5-10, Miami, Florida, USA}, interhash = {9d0db145b966a0ab04bd792ace2f8356}, intrahash = {48b5197300e91f98e34800007f258178}, keywords = {Application_quality_of_service_management Automated_model_learning Design_of_software_and_systems Formal_architecture_modeling Online_monitoring_and_forecasting Performance Prediction Resource_management SOA Self-adaptive-systems Self-aware-computing descartes t_visionposition}, month = {July}, publisher = {IEEE Computer Society}, timestamp = {2020-10-20T15:30:09.000+0200}, title = {{Towards self-aware performance and resource management in modern service-oriented systems}}, year = 2010 }