Publications

A Comparative Study of DASH Representation Sets Using Real User Characteristics
C. Kreuzberger, B. Rainer, H. Hellwagner, L. Toni and P. Frossard
Published at NOSSDAV 2016 (co-located with MMSyS 2016), Klagenfurt, Austria, May 2016.

Link to Paper: PDF
BibTeX Cite: To Appear
Presentation: PDF

Paper Website: http://concert.itec.aau.at/NOSSDAV_2016/
Git Repo: https://github.com/ChristianKreuzberger/amust-ndnSIM

Dataset URL: http://concert.itec.aau.at/SVCDataset/
Toolchain @ Github
BibTeX for citation

Paper Download Link: TBA (March 2015)

Abstract: With video streaming becoming more and more popular, the number of devices that are capable of streaming videos over the Internet is growing. This leads to a heterogeneous device landscape with varying demands. Dynamic Adaptive Streaming over HTTP (DASH) offers an elegant solution to these demands. Smart adaptation logics are able to adjust the clients' streaming quality according to several (local) parameters. Recent research indicated benefits of blending Scalable Video Coding (SVC) with DASH, especially considering Future Internet architectures. However, except for a DASH dataset with a single SVC encoded video, no other datasets are publicly available. The contribution of this paper is two-fold. First, a DASH/SVC dataset, containing multiple videos at varying bitrates and spatial resolutions including 1080p, is presented. Second, a toolchain for multiplexing SVC encoded videos is provided, therefore making our results reproducible and allowing researchers to generate their own datasets.