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Feida Liu

dblp:425/3632 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0004-1453-3585ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Content delivery and video streaming · 77% Network performance modeling · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Content delivery and video streaming
interactive video streaming
0.912025
Themis: Toward Stable Near-Zero Queuing Delay in Congestion Control for Low-Latency Interactive Video Streaming · ACM Multimedia 2025
Network performance modeling › delay analysis
queueing delay
0.312025
Themis: Toward Stable Near-Zero Queuing Delay in Congestion Control for Low-Latency Interactive Video Streaming · ACM Multimedia 2025

Methods — techniques the papers use, named apart from their topics

utility feedback · 0.9three-phase bitrate adjustment · 0.9adaptive pacing · 0.9
YearPublicationVenuePosition
2025 Themis: Toward Stable Near-Zero Queuing Delay in Congestion Control for Low-Latency Interactive Video Streaming
abstract
Low-latency interactive video streaming services critically depend on robust congestion control algorithms (CCA). However, existing CCAs often exhibit frequent self-induced oscillations from unconstrained probing, causing periodic heavy queuing and degrading the user experience. We propose Themis, a novel end-to-end CCA designed to achieve stabilized near-zero queuing delay with high bitrate. By precisely quantifying the trade-off between bitrate and queuing delay within a utility feedback mechanism, Themis effectively controls the amplitude and frequency of probing while ensuring fairness. In parallel, Themis incorporates the awareness of the queuing state through an adaptive-pacing method, combined with utility feedback to guide a three-phase bitrate adjustment strategy. This enables rapid and stable convergence to the optimal utility. We implemented Themis in QUIC, evaluated it on the Mahimahi and conducted a 90-day large-scale A/B test in a real-world network. Compared to state-of-the-art CCAs, Themis effectively suppresses self-induced oscillations, increases the average frame bitrate by 66.8%, and reduces the average frame delay by 13.5%, demonstrating a superior trade-off between high bitrate and low queuing delay.
Feida Liu, Jiaqi Zheng 0001, Boxi Liu, Guihai Chen
ACM Multimedia1