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Record W2102449606 · doi:10.1109/glocom.1994.513581

An experimental study of video traffic on an Ethernet local area network

2002· article· en· W2102449606 on OpenAlexaff
Sanjeev Gupta, Carey Williamson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsComputer scienceComputer networkCarrier EthernetEthernet over SDHUncompressed videoSynchronous EthernetMetro EthernetLocal area networkATA over EthernetEthernet flow controlIntegrated Services Digital NetworkBottleneckVideo qualityEthernetEthernet over PDHReal-time computingVideo processingEmbedded systemVideo trackingComputer hardwareEngineering

Abstract

fetched live from OpenAlex

Video applications and multimedia services will likely be the largest consumers of bandwidth on future high speed networks, such as B-ISDN/ATM. This paper presents an empirical study of a continuous bit rate video application (VideoPix) on an existing (low speed) 10 Mbps Ethernet local area network. The performance of the application is found to be poor in terms of the quality (i.e., frame rate) of the video delivered to clients of the video server. However, a detailed analysis of the network traffic produced by the application shows that the network itself is not the performance bottleneck. Rather, the performance is limited by display technology, the X window system, and TCP/IP. If these performance limits could be overcome, a single uncompressed video application would easily consume all the available bandwidth on an Ethernet local area network.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.251
Teacher spread0.226 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2002
Admission routes1
Has abstractyes

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