Design for a Generic Knowledge Base for Autonomic QoE Optimization in Multimedia Access Networks

The management of access networks to guarantee the Quality of Experience for multiplay services, is complicated by the heterogeneity in service specifics and home network configurations. The appropriate action to restore the QoE is highly dependent on the type of service, the affected user, etc. This requires an almost per-user and per-service management. Through autonomous reasoning, the required QoE restorative actions for underperforming services can be determined in a scalable way. This reasoning process needs a solid knowledge base, containing information about the network, the services and the QoE restorative actions that can be undertaken. This article gives an overview of these requirements and presents an OWL/SWRL based knowledge base that can be used in an autonomous QoE management architecture for the access network. Besides storing all information, the proposed knowledge base will autonomously deduce new information. This new information can be used to raise alarms to higher layers in the architecture or to autonomously propose QoE restorative actions for underperforming services.