Analysis of QoE for Adaptive Video Streaming over Wireless Networks with User Abandonment Behavior

Rachid El-Azouzi (1) , Krishna Acharya (2) , Sudheer Poojary (1) , Albert Sunny (3) , Majed Haddad (1) , Eitan Altman (3, 4, 1, 5) , Dimitrios Tsilimantos (6) , Stefan Valentin (7)

1 LIA - Laboratoire Informatique d'Avignon
2 ENS de Lyon - École normale supérieure de Lyon
3 NEO - Network Engineering and Operations
4 COMUE UCA - COMUE Université Côte d'Azur (2015-2019)
5 LINCS - Laboratory of Information, Network and Communication Sciences
6 Huawei Technologies France
7 TU Darmstadt - Technische Universität Darmstadt - Technical University of Darmstadt

In this paper, we develop an analytical framework to compute the Quality-of-Experience (QoE) metrics of video streaming in wireless networks. Our framework takes into account the system dynamics that arises due to the arrival and departure of flows. We also consider the possibility of users abandoning the system on account of poor QoE. Considering the coexistence of multiple services such as video streaming and elastic flows, we use a Markov chain based analysis to compute the user QoE metrics: probability of starvation, prefetching delay, average video quality and bitrate switching. Our simulation results validate the accuracy of our model and describe the impact of scheduler at eNB on the QoE metrics.

Domaines: Informatique et théorie des jeux [cs.GT]

Rachid El-Azouzi, Krishna Acharya, Sudheer Poojary, Albert Sunny, Majed Haddad, et al.. Analysis of QoE for Adaptive Video Streaming over Wireless Networks with User Abandonment Behavior. WCNC 2019 - IEEE Wireless Communications and Networking Conference, Apr 2019, Marrakesh, Morocco. pp.1-8, ⟨10.1109/WCNC.2019.8885491⟩. ⟨hal-02418543⟩