TY - GEN
T1 - Short Video Streaming With Data Wastage Awareness
AU - Zhang, Guanghui
AU - Liu, Ke
AU - Hu, Haibo
AU - Guo, Jing
N1 - Funding Information:
* Corresponding author: Haibo Hu ([email protected]) This work is supported by Centre for Advances in Reliability and Safety Limited (CAiRS) under AIR@InnoHK research cluster, General Program of National Natural Science Foundation of China 62072439, and Shandong Provincial Natural Science Foundation ZR2019LZH004.
Publisher Copyright:
© 2021 IEEE
PY - 2021/7
Y1 - 2021/7
N2 - Fueled by emerging short video applications (e.g., TikTok), streaming short videos is now ubiquitous among mobile users. A major problem in short video streaming is data wastage, i.e., the downloaded video data is not watched but discarded due to video switching, so the bandwidth consumed in video transferring is wasted. Our measurements show that 45.2% of video data is wasted in practice, which is a significant proportion that can lead to tremendous financial loss. To tackle the problem, this work develops a novel algorithm called Wastage Aware Streaming (WAS) which learns viewing behaviors and network conditions to reduce data wastage while keeping Quality-of-Experience (QoE) intact. Extensive evaluations show that WAS can substantially reduce data wastage, e.g., 70%, without any adverse impact on QoE, thus it offers a practical solution for data wastage in short video services.
AB - Fueled by emerging short video applications (e.g., TikTok), streaming short videos is now ubiquitous among mobile users. A major problem in short video streaming is data wastage, i.e., the downloaded video data is not watched but discarded due to video switching, so the bandwidth consumed in video transferring is wasted. Our measurements show that 45.2% of video data is wasted in practice, which is a significant proportion that can lead to tremendous financial loss. To tackle the problem, this work develops a novel algorithm called Wastage Aware Streaming (WAS) which learns viewing behaviors and network conditions to reduce data wastage while keeping Quality-of-Experience (QoE) intact. Extensive evaluations show that WAS can substantially reduce data wastage, e.g., 70%, without any adverse impact on QoE, thus it offers a practical solution for data wastage in short video services.
KW - Data wastage
KW - Mobile network
KW - Quality-of-Experience
KW - Short video streaming
KW - Video reliability
UR - http://www.scopus.com/inward/record.url?scp=85126451442&partnerID=8YFLogxK
U2 - 10.1109/ICME51207.2021.9428379
DO - 10.1109/ICME51207.2021.9428379
M3 - Conference article published in proceeding or book
AN - SCOPUS:85126451442
T3 - Proceedings - IEEE International Conference on Multimedia and Expo
SP - 1
EP - 6
BT - 2021 IEEE International Conference on Multimedia and Expo, ICME 2021
PB - IEEE Computer Society
T2 - 2021 IEEE International Conference on Multimedia and Expo, ICME 2021
Y2 - 5 July 2021 through 9 July 2021
ER -