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Record W2473226904 · doi:10.4018/ijmdem.2016070102

A Dynamic Approach to Estimate Receiving Bandwidth for WebRTC

2016· article· en· W2473226904 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Multimedia Data Engineering and Management · 2016
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsWebRTCComputer scienceThe InternetNetwork congestionBandwidth (computing)Packet lossComputer networkNetwork packetWeb browserWorld Wide Web

Abstract

fetched live from OpenAlex

Web Real-Time Communication (WebRTC), drafted by the World Wide Web Consortium (W3C) and Internet Engineering Task Force (IETF), enables direct browser-to-browser real-time communication. As its congestion control mechanism, WebRTC uses the Google Congestion Control (GCC) algorithm. But using GCC will limit WebRTC's performance in cases of overusing due to using a fixed decreasing factor, known as alpha (a). In this paper, the authors propose a dynamic alpha model to reduce the receiving bandwidth estimate during overuse as indicated by the overuse detector. Using their proposed model, the receiver can more efficiently estimate its receiving rate in case of overuse. They implemented their model over both unconstrained and constrained networks. Experimental results show noticeable improvements in terms of higher incoming rate, lower Round-Trip Time, and lower packet loss compared to the fixed alpha model.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.982
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.265
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it