This article presents an approach and a framework designed to enable the QoS analysis of Web-service processes for real-time service provisioning (RTSP) based on service compositions. In the article, we demonstrate that it’s possible to combine QoS parameters defined on various domains to provide differentiated services, and to dynamically allocate available resources among customers while delivering high-quality multimedia content. We also demonstrate that it’s possible to customize multimedia streams to highly variable network conditions to provide acceptable quality in spite of factors possibly affecting QoS, such as network bandwidth or user frame rate when accessing the service. To achieve these objectives, we leverage our earlier work related to complex, adaptive Web-service processes to supply more information for determining the quality and size of the delivered object.2 Additionally, this article introduces an architecture that supports our approach. The architecture includes a module for predicting possible QoS faults through a machine-learning approach and a module for monitoring QoS parameters and supporting possible adaptation and recovery actions in case of failure. Our goal in presenting this work is to stimulate future research about quality of composite services in service-oriented architectures (see http://www.oasis-open.org/committees/tc_cat.php?cat=soa?). The ‘‘Related Work’’ sidebar presents other researchers’ approaches.
A Framework for Using Web Services to Enhance QoS for Content Delivery
LOPS, PASQUALE;REDAVID, DOMENICO;SEMERARO, Giovanni
2009-01-01
Abstract
This article presents an approach and a framework designed to enable the QoS analysis of Web-service processes for real-time service provisioning (RTSP) based on service compositions. In the article, we demonstrate that it’s possible to combine QoS parameters defined on various domains to provide differentiated services, and to dynamically allocate available resources among customers while delivering high-quality multimedia content. We also demonstrate that it’s possible to customize multimedia streams to highly variable network conditions to provide acceptable quality in spite of factors possibly affecting QoS, such as network bandwidth or user frame rate when accessing the service. To achieve these objectives, we leverage our earlier work related to complex, adaptive Web-service processes to supply more information for determining the quality and size of the delivered object.2 Additionally, this article introduces an architecture that supports our approach. The architecture includes a module for predicting possible QoS faults through a machine-learning approach and a module for monitoring QoS parameters and supporting possible adaptation and recovery actions in case of failure. Our goal in presenting this work is to stimulate future research about quality of composite services in service-oriented architectures (see http://www.oasis-open.org/committees/tc_cat.php?cat=soa?). The ‘‘Related Work’’ sidebar presents other researchers’ approaches.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.