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Record W2143674264 · doi:10.1109/icc.1995.525165

Virtual call admission control-a strategy for dynamic routing over ATM networks

2002· article· en· W2143674264 on OpenAlexafffund
Changming Liu, Hussein T. Mouftah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaInstituto de Telecomunicações
KeywordsComputer scienceComputer networkRouting (electronic design automation)Static routingPolicy-based routingDynamic Source RoutingDistributed computingHierarchical routingCall Admission ControlDestination-Sequenced Distance Vector routingLink-state routing protocolRouting protocolTelecommunicationsWireless network

Abstract

fetched live from OpenAlex

Routing and call admission control (CAC) mutually interact with each other in ATM networks. This interaction creates new problems for dynamic routing over ATM networks, such as that a path selected by routing may be rejected by CAC. We present a routing strategy called virtual call admission control (VCAC) to minimize these problems. For any single call, VCAC prunes the entire network topology to an effective one, based on which, routing then selects the paths. The algorithms developed for CAC are adopted for VCAC, so VCAC can precisely predict the decision to be made by CAC. We also propose a simple VCAC algorithm and compare it with other VCAC algorithm candidates based on certain criteria. Their performance is evaluated through computer simulation. The simulation results indicate that VCAC is an effective strategy for dynamic routing over ATM networks and the proposed algorithm for VCAC meets all the criteria, and therefore is a good candidate for VCAC.

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 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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.646

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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2002
Admission routes2
Has abstractyes

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