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Congestion-Based Pricing Resource Management in Broadband Wireless Networks

2010· article· en· W2124158303 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 Transactions on Wireless Communications · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceComputer networkQuality of serviceNetwork congestionNetwork traffic controlWireless broadbandWireless networkFairness measureProvisioningBandwidth allocationWirelessNetwork packetTelecommunicationsThroughput

Abstract

fetched live from OpenAlex

Supporting the diverse QoS requirements of multimedia applications is an essential requirement for broadband wireless access (BWA) networks. Due to the projected dynamics in traffic patterns, more capable resource management functionalities are needed. We propose a game-theoretic, congestion-based pricing scheduler that incorporates two sub-schemes: a bandwidth provisioning sub-scheme to address the bandwidth scarcity to provision in fourth generation (4G) BWA technologies and an efficient packet scheduler sub-scheme. To the best of our knowledge, the proposed scheduler is the first one to simultaneously control congestion and fairness while providing differentiated QoS guarantees in BWA networks. Simulation results show that the proposed scheme realizes our objectives of controlling congestion, providing differentiated QoS guarantees, and catering to proportional fairness among the different network classes and among connections within the same class.

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: none
Teacher disagreement score0.933
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 science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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