Load-Adjusted Video Quality Prediction Methods for Missing Data

Ruairí de Fréin

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    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.
    Original languageEnglish
    Title of host publication 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST)
    Pages1-6
    ISBN (Electronic)978-1-9083-2052-0, 978-1-9083-2051-3
    DOIs
    Publication statusAccepted/In press - 2015

    Publication series

    Name2015 10th International Conference for Internet Technology and Secured Transactions (ICITST)

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