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Record W2090709584 · doi:10.1109/jsac.2012.120222

A Distributed Multi-Service Resource Allocation Algorithm in Heterogeneous Wireless Access Medium

2012· article· en· W2090709584 on OpenAlexaff
Muhammad Ismail, Weihua Zhuang

Bibliographic record

VenueIEEE Journal on Selected Areas in Communications · 2012
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceMultihomingBase stationComputer networkWireless networkResource allocationRadio resource managementWirelessAlgorithmBandwidth (computing)Heterogeneous networkDistributed computingTelecommunicationsThe Internet

Abstract

fetched live from OpenAlex

In this paper, radio resource allocation in a heterogeneous wireless access medium is studied. Mobile terminals (MTs) are assumed to have multi-homing capabilities. Both constant bit rate and variable bit rate services are considered. A novel algorithm is developed for the resource allocation. Unlike existing solutions in literature, the proposed algorithm is distributed in nature, such that each network base station / access point can perform its own resource allocation to support the MTs according to their service classes. The coordination among different available wireless access networks' base stations is established via the MT multiple radio interfaces in order to provide the required bandwidth to each MT. A priority mechanism is employed, so that each network gives a higher priority on its resources to its own subscribers as compared to other users. Numerical results demonstrate the validity of the proposed algorithm.

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)0.001
metaresearch head score (Gemma)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.358
Teacher spread0.278 · 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

Citations135
Published2012
Admission routes1
Has abstractyes

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