Towards an autonomic architecture for optimising the QoE in access networks

Multimedia services over broadband DSL access and aggregation networks such as Broadcast TV and Video on Demand have gained a lot of popularity in the last few years. Operators who want to maximise their revenue try to manage the service quality as perceived by the end user, commonly described as the Quality of Experience (QoE). This QoE management is further complicated by the heterogeneity of today’s access and aggregation networks, triggering a QoE management on a per service or per subscriber basis. This introduces the need for detailed knowledge about users and services. In our research, we are focusing on an architecture for effectively partitioning this knowledge in an autonomic management environment. The problem of organising knowledge in an autonomic network has been addressed through the Knowledge Based Network paradigm [1]. In a Knowledge Based Network, producers of information describe the available information through ontologies. Consumers subscribe to this information through semantic queries. The work presented in this paper complements this approach: while the KBN work focuses on semantic clustering of information [2] and augmenting the semantic capabilities of existing solutions [3], we focus on the automatic generation of the semantic queries, which we call