Research Article
Policy based resource management for QoS aware applications in heterogeneous network environments
@INPROCEEDINGS{10.1109/CHINACOM.2007.4469382, author={Dirk Hetzer and Ilka Miloucheva and Karl Jonas and Christian Niephaus}, title={Policy based resource management for QoS aware applications in heterogeneous network environments}, proceedings={2nd International ICST Conference on Communications and Networking in China}, publisher={IEEE}, proceedings_a={CHINACOM}, year={2008}, month={3}, keywords={QoS policy context learning heterogeneous networks ontology policy actor policy adaptation policy repository}, doi={10.1109/CHINACOM.2007.4469382} }- Dirk Hetzer
Ilka Miloucheva
Karl Jonas
Christian Niephaus
Year: 2008
Policy based resource management for QoS aware applications in heterogeneous network environments
CHINACOM
IEEE
DOI: 10.1109/CHINACOM.2007.4469382
Abstract
Dynamic configuration and adaptation of resources for QoS-aware applications in heterogeneous access network environment (UMTS, WIMAX, WLAN DVB-T, DVB-H) using automated tools is a challenge today. The focus of this paper is a toolkit for intelligent management of resource allocation in heterogeneous network infrastructures based on policies of different actors (network operator, service providers and users). Policy based management of resources for QoS-aware applications (Video-on-Demand, Mobile TV) dependent on network capabilities, context learning and preferences of the policy actors is proposed, which enhances the current state-ofthe- art and IETF standardisation. The policy management toolkit includes components for policy specification, adaptation and enforcement, which are interacting using policy repository. The design allows the automated resource adaptation for QoS based applications based on context information and hierarchical dependencies of policy actors. A learning component is integrated in order to discover the context considering measurement and monitoring data. The policy management tookit is discussed, emphasising on ontology driven policy repository design, context learning and flexible scenario-oriented management interfaces for policy specifications.
