Bandwidth Prediction Within Playback-Time of Buffer Duration Based on Frame-Level Stable Segment for Live Streaming

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Live streaming demands low latency and small rebuffering time. Existing ABR schemes often fail to meet these requirements because inaccurate bandwidth prediction degrades the performance. In this work, we propose the Frame-level Bandwidth Segmentation and Playback-time based Bandwidth Prediction (FBS-PBP) method. FBS-PBP performs bandwidth sampling at the video frame level, leverages the piecewise stability to enhance network bandwidth feature extraction, and takes the average bandwidth within the playback time of the buffer occupancy as the target to reduce rebuffering time. Simulations demonstrate that FBS-PBP significantly improves bandwidth prediction accuracy. Moreover, FBS-PBP respectively helps ThroughputRule and MPC to reduce the rebuffering ratio by 4% to 13%, and the average latency by 5.26% and 4.11%, while maintaining low latency. With the help of FBS-PBP, MPC performs as good as MERINA in terms of QoE.

Original languageEnglish
Title of host publicationWireless Artificial Intelligent Computing Systems and Applications - 19th International Conference, WASA 2025, Proceedings
EditorsZhipeng Cai, Yongxin Zhu, Yonghao Wang, Meikang Qiu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages205-216
Number of pages12
ISBN (Print)9789819687275
DOIs
StatePublished - 2025
Event19th International Conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2025 - Tokyo, Japan
Duration: 24 Jun 202526 Jun 2025

Publication series

NameLecture Notes in Computer Science
Volume15687 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2025
Country/TerritoryJapan
CityTokyo
Period24/06/2526/06/25

Keywords

  • Bandwidth prediction
  • Live streaming
  • Stable segment

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