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Record W2138129180 · doi:10.1109/vetecf.2005.1557498

Delay statistics in multi-rate wireless networks with ARQ and weighted round-robin scheduling

2006· article· en· W2138129180 on OpenAlex
Long Bao Le, Ekram Hossain, Attahiru Sule Alfa

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 institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer scienceComputer networkScheduling (production processes)Hybrid automatic repeat requestAutomatic repeat requestWireless networkWirelessTelecommunicationsMathematicsMathematical optimization

Abstract

fetched live from OpenAlex

We analyze the radio link level buffer occupancy and delay statistics in a wireless network using adaptive modulation and coding (AMC), weighted round-robin scheduling and auto- matic repeat request (ARQ)-based error control. The queueing problems for two user classes are modeled by a novel vacation queueing model, where the queue length and delay distributions can be obtained analytically. The analysis presented in this paper enables us to quantify the impacts of different channel and sys- tem parameters on the radio link performance, and to conduct cross-layer design and admission control under statistical delay constraints. We validate the analytical model, present typical nu- merical results and illustrate the usefulness of the model.

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: none
Teacher disagreement score0.488
Threshold uncertainty score0.764

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 head0.006
GPT teacher head0.198
Teacher spread0.193 · 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
Published2006
Admission routes1
Has abstractyes

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