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Record W3200373170

M. Kordi Boroujeny and B.L. Mark, "A Framework for Providing Stochastic Delay Guarantees in Communication Networks," IEEE ICC 2021 Workshop on Time-sensitive and Deterministic Networking, Montreal, Canada, June 2021

2021· article· en· W3200373170 on OpenAlexaboutno aff
Massieh Kordi Boroujeny, Brian L. Mark

Bibliographic record

VenueInternational Conference on Communications · 2021
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsNetwork calculusComputer scienceMultiplexerUpper and lower boundsNetwork packetProvisioningComputer networkTopology (electrical circuits)MultiplexingMathematical optimizationMathematicsTelecommunicationsQuality of service
DOInot available

Abstract

fetched live from OpenAlex

The provisioning of delay guarantees in packet-switched networks such as the Internet remains an important, yet challenging open problem. We propose and evaluate a framework, based on results from stochastic network calculus, for guaranteeing stochastic bounds on network delay at a statistical multiplexer. The framework consists of phase-type traffic bounds and moment generating function traffic envelopes, stochastic traffic regulators to enforce the traffic bounds, and an admission control scheme to ensure that a stochastic delay bound is maintained for a given set of flows. Through numerical examples, we show that a stochastic delay bound is maintained at the multiplexer, and contrast the proposed framework to an approach based on deterministic network calculus.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.288
Teacher spread0.258 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueInternational Conference on CommunicationsSame topicNetwork Time Synchronization TechnologiesFrench-language works237,207