Capacity planning for Web performance: metrics, models, and methods
Capacity planning for Web performance: metrics, models, and methods
Correlating resource demand information with ARM data for application services
Proceedings of the 1st international workshop on Software and performance
IEEE Transactions on Software Engineering
Parameter estimation for performance models of distributed application systems
CASCON '95 Proceedings of the 1995 conference of the Centre for Advanced Studies on Collaborative research
Introduction: Service-oriented computing
Communications of the ACM - Service-oriented computing
A model transformation framework for the automated building of performance models from UML models
Proceedings of the 5th international workshop on Software and performance
From BPMN Process Models to BPEL Web Services
ICWS '06 Proceedings of the IEEE International Conference on Web Services
A model-driven approach to describe and predict the performance of composite services
WOSP '07 Proceedings of the 6th international workshop on Software and performance
A WSDL extension for performance-enabled description of web services
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
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Distributed applications are rapidly converging towards the adoption of a computing paradigm based on service-oriented architectures, according to which an application can be seen as a composite web service that is built by assembling a set of existing services, executed on internetworked server hosts. In such a context, service providers are strategically interested both to describe the performance characteristics of offered services, to better qualify their offer and gain a significant advantage in the global marketplace; and to predict the level of performance that can be offered to service consumers. To this purpose, the paper introduces a framework for the management of performance parameters, defining the architecture that enables service providers to measure and make available performance information about the offered services. On the other hand the proposed approach allows the service consumers to automatically retrieve the performance data and then use such data to apply model-driven approaches for the performance analysis of composite web services.