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Record W1917200568 · doi:10.3233/scc-2001-232

On‐board scheduling for multimedia applications

2001· article· en· W1917200568 on OpenAlexaff
Martin Coté, Colin Black, Augustin Iuoras

Bibliographic record

VenueSpace Communications · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsSte. Anne's Hospital
Fundersnot available
KeywordsTelecommunications linkComputer scienceTime division multiple accessComputer networkQuality of serviceScheduling (production processes)BroadbandMulti-frequency time division multiple accessBandwidth (computing)Bandwidth allocationDynamic bandwidth allocationBroadband networksTelecommunicationsOrthogonal frequency-division multiplexingEngineering

Abstract

fetched live from OpenAlex

This paper discusses on‐board dynamic bandwidth allocation for satellite OBP‐based broadband multimedia interactive applications. The paper presents a bandwidth allocation scheme which is oriented towards guaranteeing the Quality of Service (QoS) associated with, but not limited to, the various traffic services/classes as defined by the ATM forum. A novel uplink (UL) access scheme is proposed, based on a Multi‐Frequency Time Division Multiple Access (MF‐TDMA) primary access scheme. The uplink access protocol derived from the proposed scheme can be supported directly on board by the means of the scheduler function. The performance of the uplink access scheme has been evaluated through extensive simulations and sample results are presented and commented. EMS’ heritage on both ground and OBP‐based schedulers is also presented.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.075
GPT teacher head0.400
Teacher spread0.325 · 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

Citations4
Published2001
Admission routes1
Has abstractyes

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