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Record W2413417445

Optimal linear-time uplink scheduling algorithms for WiMAX

2008· article· en· W2413417445 on OpenAlex
Arezou Mohammadi, Selim G. Akl, Firouz Behnamfar

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsTelecommunications linkWiMAXComputer scienceScheduling (production processes)Network packetMathematical optimizationWirelessFair-share schedulingLinear programmingHeuristicDistributed computingAlgorithmComputer networkMathematicsTelecommunicationsQuality of serviceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we focus on a recent application of realtime scheduling in wireless communications industry; namely, uplink scheduling for WiMAX systems. More specifically, we address the problem of maximizing the number of data packets to be sent in uplink such that the expectations from the system are guaranteed. We argue that this problem is NP-Complete. Thus far, only a number of heuristic algorithms have been developed for special cases of the problem and the problem has not been modeled formally. In this work, we present two formal models for the system. We take advantage of the properties of the application and derive an algorithm for uplink scheduling which has two highly favourable features: it finds the optimal solution in linear time.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.033
Threshold uncertainty score0.648

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 head0.017
GPT teacher head0.236
Teacher spread0.219 · 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

Quick stats

Citations1
Published2008
Admission routes1
Has abstractyes

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