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Record W1840441498 · doi:10.1109/ccece.1995.528068

Implementation of a window-based scheduler in an ATM switch

2002· article· en· W1840441498 on OpenAlexaff
A. Sabaa, Hani Elgebaly, E. El-Guibaly, J.C. Muzio, D.J. Shpak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceQuality of serviceComputer networkQueueScheduling (production processes)Asynchronous Transfer ModePriority queueQueueing theoryPacket switchingNetwork packetReal-time computingDistributed computingEngineering

Abstract

fetched live from OpenAlex

ATM networks have to handle a wide range of traffic characteristics and performance requirements. The transmission control scheme should regulate the flow of packets from the switching queues to the outgoing links. The quality of service (QoS) requirements can be provided by delivering the cell within a maximum predetermined delay and without exceeding the maximum limit of allowable cell loss. We propose a switching scheme to satisfy different QoS requirements. The basic buffering component of the switch is a virtual dual-ported memory shared by all input and output lines. Cells arriving on input lines are stored to the common memory. The memory is divided into multiple priority queues to handle different classes of services. Cells are simultaneously retrieved from the priority queues and transmitted over the output lines. The higher priority queues can send a predefined number of cells before the lower priority queues are serviced in order to maintain the Qos of each class. The architecture of the switch is described. A simulation for the switch is run to show the effect of the scheduling protocol on the performance metrics.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.456

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 head0.033
GPT teacher head0.286
Teacher spread0.253 · 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
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

Citations1
Published2002
Admission routes1
Has abstractyes

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