MétaCan
Menu
Back to cohort
Record W2141749523 · doi:10.1109/icc.1995.525181

A real-time call admission control algorithm in high-speed networks

2002· article· en· W2141749523 on OpenAlexaff
Shanzeng Guo, N.D. Georganas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNetwork calculusComputer scienceQuality of serviceComputer networkScheduling (production processes)Network packetAdmission controlCall Admission ControlEnd-to-end delayNode (physics)Network delayRouting (electronic design automation)Upper and lower boundsEnhanced Data Rates for GSM EvolutionReal-time computingDistributed computingMathematical optimizationWireless networkWirelessMathematicsEngineering

Abstract

fetched live from OpenAlex

A real-time call admission control algorithm is developed for admitting real time traffic streams with quality of service (QoS) constraints in high-speed networks operating in a packet-switched mode under a fixed routing strategy. The theory developed is based on a calculus for network delay at each network node with general traffic arrival process at the network edge. The authors give the necessary and sufficient conditions for the schedulability of real-time connections at each network node under non-preemptive earliest-due date scheduling policy for deterministic QoS guarantees. These necessary and sufficient conditions form the mathematical basis for the deterministic QoS guarantees in real-time communication services. The manner in which the end-to-end delay bound is to be divided into local delay bounds which together satisfy the end-to-end QoS requirements is finally proposed.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
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 head0.007
GPT teacher head0.199
Teacher spread0.191 · 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 designSimulation or modeling
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

Citations2
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicNetwork Traffic and Congestion ControlFrench-language works237,207