Multimedia streaming means delivering continuous data to a plethora of client devices. Besides the actual data transport, this also needs a high degree of content adaptation respecting the end users’ needs given by content preferences, transcoding constraints, and device capabilities. Such adaptations can be performed in many ways, usually on the media server. However, when it comes to content editing, like mixing in subtitles or picture-in-picture composition, relying on third party service providers may be necessary. For economic reasons this should be done in a service-oriented way, because a lot of adaptation modules can be reused within different adaptation workflows. Although service-oriented architectures have become widely accepted in the Web community, the multimedia environment is still dominated by monolithic systems. The main reason is the insufficient support for working with continuous data: generally the suitability of Web services for handling complex data types and state-full applications is still limited. In this paper we discuss extensions of Web service frameworks, and present a first implementation of a service-oriented framework for media streaming and digital item adaptation. The focus lies on the technical realization of the services. Our experimental results show the practicality of the actual deployment of service-oriented multimedia frameworks. Full article

This paper deals with an autonomous cognitive network management architecture which aims at achieving inter-network (horizontal) and inter-layer (vertical) cross-optimization. The proposed architecture is based on the so-called Cognitive Managers transparently embedded in properly selected network nodes. The core of each Cognitive Manager are the so-called thinking modules, which are in charge of taking consistent and coordinated decisions according to a fully cognitive approach. The thinking modules potentially avail of information coming from both the transport and the service/content layers of all networks and, based on all this inter-layer and inter-network information, take consistent and coordinated decisions impacting the different layers, aiming at the overall inter-layer, inter-network optimization. Full article