PeQAS: Personalized and high QoE video services with Adaptive distributed Streaming

• Forschungsstelle: INNOSUISSE
• Projektnummer: 13175.1 PFES-ES
• Projekttitel Englisch: PeQAS: Personalized and high QoE video services with Adaptive distributed Streaming

Kurzbeschreibung (Deutsch)

PeQAS: Personalized and high QoE video services with Adaptive distributed Streaming

Kurzbeschreibung (Englisch)

PeQAS: Personalized and high QoE video services with Adaptive distributed Streaming

Abstract (Deutsch)

As demand increases clearly faster than network resources, the advent of new high quality multimedia services goes through the development of effective coding and streaming solutions that are able to smartly use the resource at hand. This is exctaly the objective of this project, which aims at designing completely novel systems for personalized video delivery services in heterogeneous networks with source and path diversity. While large-scale networks with different channels become predominant, personalization of content is definitely getting more|and more importance in multimedia services: users are interested to receive only the information they want in a given context or networking environment. Both factors trigger the need for completely novel solutions so that the Quality of Experience (QoE) can reach acceptable levels in multimedia communication applications. This project proposes to take the best out of the network resources by innovative coding algorithms and smart streaming solutions that are able to exploit path and source diversity existing in most network architectures. Such an objective will be realized with a combination of resource and content adaptive algorithms for coding, caching,|scheduling and routing the multimedia information streams. These algorithms implemented at servers or properly selected nodes in the network will jointly participate to improving the|network utility and will increase the QoE in personalized video services in the next generation of Cisco media architectures.

Abstract (Englisch)

As demand increases clearly faster than network resources, the advent of new high quality multimedia services goes through the development of effective coding and streaming solutions that are able to smartly use the resource at hand. This is exctaly the objective of this project, which aims at designing completely novel systems for personalized video delivery services in heterogeneous networks with source and path diversity. While large-scale networks with different channels become predominant, personalization of content is definitely getting more|and more importance in multimedia services: users are interested to receive only the information they want in a given context or networking environment. Both factors trigger the need for completely novel solutions so that the Quality of Experience (QoE) can reach acceptable levels in multimedia communication applications. This project proposes to take the best out of the network resources by innovative coding algorithms and smart streaming solutions that are able to exploit path and source diversity existing in most network architectures. Such an objective will be realized with a combination of resource and content adaptive algorithms for coding, caching,|scheduling and routing the multimedia information streams. These algorithms implemented at servers or properly selected nodes in the network will jointly participate to improving the|network utility and will increase the QoE in personalized video services in the next generation of Cisco media architectures.