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Record W1996617692 · doi:10.1177/0037549702078003529

Design and Modeling of an Interval-based ABR Flow Control Protocol

2002· article· en· W1996617692 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSIMULATION · 2002
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAsynchronous Transfer ModeComputer scienceFlow control (data)Asynchronous communicationComputer networkDistributed computingSignaling protocolQueueing theoryQuality of serviceReal-time computing

Abstract

fetched live from OpenAlex

A novel flow control protocol is presented for Availability Bit Rate (ABR) service in Asynchronous Transfer Mode (ATM) networks. This scheme features periodic explicit rate feedback that enables precise allocation of link bandwidth and buffer space on a hop-by-hop basis to guarantee maximum throughput, minimum cell loss, and high resource efficiency. With the inclusion of resource management cell synchronization and consolidation algorithms, this protocol is capable of controlling point-to-multipoint ABR services within a unified framework. The authors illustrate the modeling of single ABR connection, the interaction between multiple ABR connections, and the constraints applicable to flow control decisions. A loss-free flow control mechanism is presented for high-speed ABR connections using a fluid traffic model. Supporting algorithms and ATM signaling procedures are specified, in company with linear system modeling, numerical analysis, and simulation results, which demonstrate its performance and cost benefits in high-speed backbone networking scenarios.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score0.276

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 science0.0000.000
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 head0.043
GPT teacher head0.278
Teacher spread0.235 · 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