earticle

영어

In this publication we present Immersive Networking as a novel framework for connecting people and places and things in virtual environments with augmented reality to be used in eg. Virtual training environments. The research is mandated by technology advances in internetworking underpinned by 5G networks and Internet-of-Things. These advances present new possibilities and challenges to integrate people, places and things in virtual environments. Existing frameworks such as MPEG-V possess representational capabilities but have insufficient support for integrating entities from the real world via heterogeneous infrastructure. MPEG-V for instance makes no statements about distributed control. Seamless experiences in virtual environment require self-organization of connectivity between people, places and things via heterogeneous 5G and Internet-of-Things infrastructures. A second important aspect of the quality of our experience is the immediacy of responses. Both aspects of seamless and self-organizing connections between entities require that we push control to the end-devices co-located with the entities themselves. These end-devices may incorporate sensing gateways and interaction devices, which include both local and non-local information from the virtual environment in the interaction. Thus delegation of control to end-devices requires means for the organizing or relations and clustering by relevance. This capability is particularly important as the projected number of devices and sensors to be connected via the Internet-of-Things is projected to be in the order of 50 billion by 2020. Immersive Networking supported by MediaSense [1] constitutes a scalable self-organizing means for connecting people and places and things in virtual environments with augmented reality. MediaSense moves control to the edge enabling immediacy in experiences based on seamless self-organization through clustering of entities in relations organized by relevance. We conclude by validating our approach in several scenarios evaluating the relevance and application in human decision-making.