TY - GEN
T1 - FRAB
T2 - 2021 IEEE International Conference on Communications, ICC 2021
AU - Wei, Bo
AU - Song, Hang
AU - Katto, Jiro
N1 - Funding Information:
This research is supported by JSPS KAKENHI Grant Number 20K14740 and Waseda University Grant for Special Research Projects (Project Number: 2020C-608).
Publisher Copyright:
© 2021 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - Dynamic adaptive streaming over HTTP (DASH) has been widely adopted in modern video streaming services. In DASH, the core technique is adaptive bitrate (ABR) control which can adjust the requested video bitrate level according to the network conditions to tradeoff between video quality and rebuffering risk. It is a challenge for the ABR methods in the scenarios when multiple DASH streaming users compete over the network bottleneck. This paper proposes a client-side ABR control method, flexible relaxation assisted by buffer (FRAB), to achieve fair, stable and efficient video streaming among different users. The idea of FRAB is to relax the change of the video quality based on current buffer level, which can enhance the stability of video streaming. Meanwhile, by flexibly adjusting the relaxation, the efficiency and fairness among all users are improved. FRAB is evaluated in real experiments under three different network conditions and compared with conventional multi-user ABR algorithms. Results indicate FRAB has the best performance in fairness, which reduces the unfairness by a maximum of 69.5% under real-world measured network condition. It also improves the efficiency by 71.3% comparing with PANDA, and enhances the stability by 73.3% comparing with TFDASH. The experiment results demonstrated that the proposed method has superior performances in multi-user DASH video streaming.
AB - Dynamic adaptive streaming over HTTP (DASH) has been widely adopted in modern video streaming services. In DASH, the core technique is adaptive bitrate (ABR) control which can adjust the requested video bitrate level according to the network conditions to tradeoff between video quality and rebuffering risk. It is a challenge for the ABR methods in the scenarios when multiple DASH streaming users compete over the network bottleneck. This paper proposes a client-side ABR control method, flexible relaxation assisted by buffer (FRAB), to achieve fair, stable and efficient video streaming among different users. The idea of FRAB is to relax the change of the video quality based on current buffer level, which can enhance the stability of video streaming. Meanwhile, by flexibly adjusting the relaxation, the efficiency and fairness among all users are improved. FRAB is evaluated in real experiments under three different network conditions and compared with conventional multi-user ABR algorithms. Results indicate FRAB has the best performance in fairness, which reduces the unfairness by a maximum of 69.5% under real-world measured network condition. It also improves the efficiency by 71.3% comparing with PANDA, and enhances the stability by 73.3% comparing with TFDASH. The experiment results demonstrated that the proposed method has superior performances in multi-user DASH video streaming.
KW - DASH
KW - adaptive bitrate control
KW - fairness
KW - flexible relaxation method
KW - multiple users
UR - http://www.scopus.com/inward/record.url?scp=85115713160&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85115713160&partnerID=8YFLogxK
U2 - 10.1109/ICC42927.2021.9500784
DO - 10.1109/ICC42927.2021.9500784
M3 - Conference contribution
AN - SCOPUS:85115713160
T3 - IEEE International Conference on Communications
BT - ICC 2021 - IEEE International Conference on Communications, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 June 2021 through 23 June 2021
ER -