With the introduction of services, systems become more flexible as new services can easily be composed out of existing services. Services are increasingly used in mission-critical systems and applications and therefore considering Quality of Service (QoS) properties is an essential part of the service selection. Quality prediction techniques support the service provider in determining possible QoS levels that can be guaranteed to a customer or in deriving the operation costs induced by a certain QoS level. In this chapter, we present an overview on our work on modeling service-oriented systems for performance prediction using the Palladio Component Model. The prediction builds upon a model of a service-based system, and evaluates this model in order to determine the expected service quality. The presented techniques allow for early quality prediction, without the need for the system being already deployed and operating. We present the integration of our prediction approach into an SLA management framework. The emerging trend to combine event-based communication and Service-Oriented Architecture (SOA) into Event-based SOA (ESOA) induces new challenges to our approach, which are topic of a special subsection.
%0 Conference Proceedings
%1 rathfelder2010c
%A Rathfelder, Christoph
%A Klatt, Benjamin
%A Brosch, Franz
%A Kounev, Samuel
%B Handbook of Research on Service-Oriented Systems and Non-Functional Properties: Future Directions
%C Hershey, PA, USA
%D 2011
%E Reiff-Marganiec, Stephan
%E Tilly, Marcel
%I IGI Global
%K Analytical_and_simulation-based_analysis Application_quality_of_service_management Formal_architecture_modeling Meta-models Performance Prediction SOA Simulation descartes se2_book t_bookchapter
%P 258--279
%T Performance Modeling for Quality of Service Prediction in Service-Oriented Systems
%U http://www.igi-global.com/chapter/handbook-research-service-oriented-systems/60889
%X With the introduction of services, systems become more flexible as new services can easily be composed out of existing services. Services are increasingly used in mission-critical systems and applications and therefore considering Quality of Service (QoS) properties is an essential part of the service selection. Quality prediction techniques support the service provider in determining possible QoS levels that can be guaranteed to a customer or in deriving the operation costs induced by a certain QoS level. In this chapter, we present an overview on our work on modeling service-oriented systems for performance prediction using the Palladio Component Model. The prediction builds upon a model of a service-based system, and evaluates this model in order to determine the expected service quality. The presented techniques allow for early quality prediction, without the need for the system being already deployed and operating. We present the integration of our prediction approach into an SLA management framework. The emerging trend to combine event-based communication and Service-Oriented Architecture (SOA) into Event-based SOA (ESOA) induces new challenges to our approach, which are topic of a special subsection.
@proceedings{rathfelder2010c,
abstract = {With the introduction of services, systems become more flexible as new services can easily be composed out of existing services. Services are increasingly used in mission-critical systems and applications and therefore considering Quality of Service (QoS) properties is an essential part of the service selection. Quality prediction techniques support the service provider in determining possible QoS levels that can be guaranteed to a customer or in deriving the operation costs induced by a certain QoS level. In this chapter, we present an overview on our work on modeling service-oriented systems for performance prediction using the Palladio Component Model. The prediction builds upon a model of a service-based system, and evaluates this model in order to determine the expected service quality. The presented techniques allow for early quality prediction, without the need for the system being already deployed and operating. We present the integration of our prediction approach into an SLA management framework. The emerging trend to combine event-based communication and Service-Oriented Architecture (SOA) into Event-based SOA (ESOA) induces new challenges to our approach, which are topic of a special subsection.},
added-at = {2020-04-05T23:14:02.000+0200},
address = {Hershey, PA, USA},
author = {Rathfelder, Christoph and Klatt, Benjamin and Brosch, Franz and Kounev, Samuel},
biburl = {https://www.bibsonomy.org/bibtex/2f6250c04a7b1d9072c68936c1c995079/se-group},
booktitle = {{Handbook of Research on Service-Oriented Systems and Non-Functional Properties: Future Directions}},
editor = {Reiff-Marganiec, Stephan and Tilly, Marcel},
interhash = {35d0b094b7387d09cbc175a95afc3fd5},
intrahash = {f6250c04a7b1d9072c68936c1c995079},
keywords = {Analytical_and_simulation-based_analysis Application_quality_of_service_management Formal_architecture_modeling Meta-models Performance Prediction SOA Simulation descartes se2_book t_bookchapter},
month = {December},
pages = {258--279},
publisher = {IGI Global},
timestamp = {2021-01-26T14:21:52.000+0100},
title = {{P}erformance {M}odeling for {Q}uality of {S}ervice {P}rediction in {S}ervice-{O}riented {S}ystems},
url = {http://www.igi-global.com/chapter/handbook-research-service-oriented-systems/60889},
year = 2011
}