An Analytical Framework for Video Quality and Excess Data Distribution in Multiple-Quality Video Under Dynamic Channel Conditions

Mehmet Akif Yazici

doi:10.1007/978-3-030-91825-5_29

An Analytical Framework for Video Quality and Excess Data Distribution in Multiple-Quality Video Under Dynamic Channel Conditions

Mehmet Akif Yazici^*

^*Corresponding author for this work

Informatics Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present an analytical framework to obtain the distribution of frozen, low quality, and high quality video in a setting with two video quality levels where the channel is dynamic and the data rate the user can achieve varies with time. The presented model, which is based on multi-regime Markov fluid queues, is also capable of producing the distribution of the excess data present in the playout buffer at the end of the video session duration, which will be wasted. The playout control is assumed to be hysteretic, and the effects of the values of thresholds selected for starting playout, switching to low/high quality levels, and pausing/resuming download on the distribution of video quality and excess data is investigated. The presented model can be extended to quality levels more than two.

Original language	English
Title of host publication	Performance Engineering and Stochastic Modeling - 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, Proceedings
Editors	Paolo Ballarini, Hind Castel, Ioannis Dimitriou, Mauro Iacono, Tuan Phung-Duc, Joris Walraevens
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	472-487
Number of pages	16
ISBN (Print)	9783030918248
DOIs	https://doi.org/10.1007/978-3-030-91825-5_29
Publication status	Published - 2021
Event	17th European Performance Engineering Workshop, EPEW 2021, and the 26th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2021 - Virtual, Online Duration: 13 Dec 2021 → 14 Dec 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13104 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th European Performance Engineering Workshop, EPEW 2021, and the 26th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2021
City	Virtual, Online
Period	13/12/21 → 14/12/21

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

Markov fluid queue
Quality of experience
Video
Wasted video data

Access to Document

10.1007/978-3-030-91825-5_29

Cite this

Yazici, M. A. (2021). An Analytical Framework for Video Quality and Excess Data Distribution in Multiple-Quality Video Under Dynamic Channel Conditions. In P. Ballarini, H. Castel, I. Dimitriou, M. Iacono, T. Phung-Duc, & J. Walraevens (Eds.), Performance Engineering and Stochastic Modeling - 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, Proceedings (pp. 472-487). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13104 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-91825-5_29

Yazici, Mehmet Akif. / An Analytical Framework for Video Quality and Excess Data Distribution in Multiple-Quality Video Under Dynamic Channel Conditions. Performance Engineering and Stochastic Modeling - 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, Proceedings. editor / Paolo Ballarini ; Hind Castel ; Ioannis Dimitriou ; Mauro Iacono ; Tuan Phung-Duc ; Joris Walraevens. Springer Science and Business Media Deutschland GmbH, 2021. pp. 472-487 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Yazici, MA 2021, An Analytical Framework for Video Quality and Excess Data Distribution in Multiple-Quality Video Under Dynamic Channel Conditions. in P Ballarini, H Castel, I Dimitriou, M Iacono, T Phung-Duc & J Walraevens (eds), Performance Engineering and Stochastic Modeling - 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13104 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 472-487, 17th European Performance Engineering Workshop, EPEW 2021, and the 26th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2021, Virtual, Online, 13/12/21. https://doi.org/10.1007/978-3-030-91825-5_29

An Analytical Framework for Video Quality and Excess Data Distribution in Multiple-Quality Video Under Dynamic Channel Conditions. / Yazici, Mehmet Akif.
Performance Engineering and Stochastic Modeling - 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, Proceedings. ed. / Paolo Ballarini; Hind Castel; Ioannis Dimitriou; Mauro Iacono; Tuan Phung-Duc; Joris Walraevens. Springer Science and Business Media Deutschland GmbH, 2021. p. 472-487 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13104 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Yazici MA. An Analytical Framework for Video Quality and Excess Data Distribution in Multiple-Quality Video Under Dynamic Channel Conditions. In Ballarini P, Castel H, Dimitriou I, Iacono M, Phung-Duc T, Walraevens J, editors, Performance Engineering and Stochastic Modeling - 17th European Workshop, EPEW 2021, and 26th International Conference, ASMTA 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 472-487. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-91825-5_29