Short Video Streaming With Data Wastage Awareness

Guanghui Zhang, Ke Liu, Haibo Hu, Jing Guo

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Multimedia and Expo, ICME 2021
PublisherIEEE Computer Society
Number of pages6
ISBN (Electronic)9781665438643
Publication statusPublished - Jul 2021
Event2021 IEEE International Conference on Multimedia and Expo, ICME 2021 - Shenzhen, China
Duration: 5 Jul 20219 Jul 2021

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X


Conference2021 IEEE International Conference on Multimedia and Expo, ICME 2021


  • Data wastage
  • Mobile network
  • Quality-of-Experience
  • Short video streaming
  • Video reliability

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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