Load-Adjusted Video Quality Prediction Methods for Missing Data
2015 (English)In: 10th International Conference for Internet Technology and Secured Transactions: ICITST-2015, London, UK: IEEE Computer Society Digital Library, 2015, §-6 p.Conference paper (Refereed)
A polynomial fitting model for predicting the RTP packet rate of Video-on-Demand received by a client is presented. The approach is underpinned by a parametric statistical model for the client-server system, namely the PQ-model. It improves the robustness of the predictor in the presence of a time-varying load on the server. The advantage of our approach is that (1) if we model the load on the server, we can then use this model to improve RTP packet rate predictions; (2) we can predict how the server will behave under previously unobserved loads –a tool which is particularly useful for network planning; and finally (3) the PQ-model provides accurate predictions of future RTP packet rates in scenarios where training data is unavailable.
Place, publisher, year, edition, pages
London, UK: IEEE Computer Society Digital Library, 2015. §-6 p.
Video-on=Demand; Linear Regression; Predictive Analytics; Network Analytics
Research subject Applied and Computational Mathematics
IdentifiersURN: urn:nbn:se:kth:diva-179060DOI: 10.1109/ICITST.2015.7412111ISI: 000380391600048ScopusID: 2-s2.0-84964545609ISBN: 978-190832052-0OAI: oai:DiVA.org:kth-179060DiVA: diva2:881200
ICITST-2015,December 14-16, 2015, London, UK
QC 201606152015-12-092015-12-092016-08-23Bibliographically approved