Effcient delivery of video data over computer networks has been studied extensively for decades. Still, multi-receiver video
delivery is challenging, due to heterogeneity and variability in network availability, end node capabilities, and receiver
preferences. Our earlier work has shown that content-based networking is a viable technology for fine granularity multireceiver
video streaming. By exploiting this technology, we have demonstrated that each video receiver is provided with
fine grained and independent selectivity along the different video quality dimensions region of interest, signal to noise
ratio for the luminance and the chrominance planes, and temporal resolution. Here we propose a novel adaptation scheme
combining such video streaming with state-of-the-art techniques from the field of adaptation to provide receiver-driven
multi-dimensional adaptive video streaming. The scheme allows each client to individually adapt the quality of the received
video according to its currently available resources and own preferences. The proposed adaptation scheme is validated
experimentally. The results demonstrate adaptation to variations in available bandwidth and CPU resources roughly over
two orders of magnitude and that fine grained adaptation is feasible given radically different user preferences.
Efficient delivery of video data over computer networks has been studied extensively for decades. Still, multi-receiver video delivery represents a challenge. The challenge is complicated by heterogeneity in network availability, end node capabilities, and receiver preferences. This paper demonstrates that content-based networking is a promising technology for efficient multi-receiver
video streaming. The contribution of this work is the bridging of content-based networking with techniques from the fields of video compression and streaming. In the presented approach, each video receiver is provided with fine grained selectivity along different video quality dimensions, such as region of interest, signal to noise
ratio, colors, and temporal resolution. Efficient delivery, in terms of network utilization and end node processing requirements, is maintained. A prototype is implemented in the Java programming language and the software is available as open source. Experimental results are presented which demonstrate the feasibility of our approach.