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Record W2105474904 · doi:10.1109/vtcf.2006.275

Opportunistic QoS Enhanced Scheduler for Real-Time Traffic in Wireless Communication Systems

2006· article· en· W2105474904 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.

Bibliographic record

VenueIEEE Vehicular Technology Conference · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceComputer networkQuality of serviceNetwork packetNetwork schedulerScheduling (production processes)WirelessProvisioningThroughputBandwidth (computing)Distributed computingReal-time computingTransmission delayProcessing delayTelecommunications

Abstract

fetched live from OpenAlex

The task of a packet scheduler for real-time traffic is to ensure that packet arrivals satisfy certain quality of service (QoS) requirements. At the same time, it is necessary to make efficient use of the limited capacity of the time-varying wireless fading channel. These two requirements are often in conflict to each other. Most existing schedulers either concentrate on the effective use of the radio resource, or only focus on QoS provisioning. By introducing the concept of flexible time and urgent time period, we propose an opportunistic QoS enhanced scheduler (OQES) which tries to maximize system throughput by exploiting the time-varying channel by applying multi-user diversity as well as a "meets delay" requirement. To avoid wasting bandwidth, a simple proactive packet discarding mechanism has also been introduced to discard packets that are to be dropped. Simulation results show that OQES outperforms existing schedulers for realtime traffic.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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