Online prediction of the running time of tasks
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
On the stability of a partially accessible multi-station queue with state-dependent routing
Queueing Systems: Theory and Applications
Computer Systems Performance Evaluation and Prediction
Computer Systems Performance Evaluation and Prediction
Nonfunctional Requirements: From Elicitation to Conceptual Models
IEEE Transactions on Software Engineering
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
Model-Based Performance Prediction in Software Development: A Survey
IEEE Transactions on Software Engineering
An approach for quality of service adaptation in service-oriented Grids: Research Articles
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
Theory, Volume 1, Queueing Systems
Theory, Volume 1, Queueing Systems
A model-oriented framework for runtime monitoring of nonfunctional properties
QoSA'05 Proceedings of the First international conference on Quality of Software Architectures and Software Quality, and Proceedings of the Second International conference on Software Quality
Pre-emptive adaptation through classical control theory
QoSA'07 Proceedings of the Quality of software architectures 3rd international conference on Software architectures, components, and applications
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Service-based software architectures are often modeled with queues and queuing networks. Such models are useful for performance evaluation and design. They can also assist in runtime maintenance and administration, but, in this context, it is often far more valuable to be able to forecast how QoS characteristics are likely to evolve in the near future. This is particularly important in cases where systems can be adapted to counter QoS constraint violations: in such systems, given predictions of likely future QoS characteristics, pre-emptive adaptation strategies can be implemented. This paper outlines an approach to runtime prediction of QoS characteristics of queued systems. Predictions are computed by applying ARIMA forecasting techniques to basic properties of a queued model, and then using the model to predict complex QoS characteristics. We outline how our methods integrate into our implementation framework for monitoring and pre-emptive adaptation of web service based systems.