MétaCan
Menu
Back to cohort
Record W4254557178 · doi:10.1002/wcm.695

On the effect of reservation period on performance of IEEE 802.16 R‐MAC protocol

2008· article· en· W4254557178 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

VenueWireless Communications and Mobile Computing · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceReservationComputer networkNetwork packetThroughputAccess controlBandwidth (computing)TelecommunicationsWireless

Abstract

fetched live from OpenAlex

Abstract The IEEE 802.16 standard is gaining broad consideration to serve the expanding demand for broadband access networks. In this standard, the best effort traffic uses the reservation multiple access control (MAC) mechanism, which is widely adopted in recent broadband network technologies. The goal of this paper is to study the performance of the MAC protocol of the best effort traffic in the IEEE 802.16 standard with emphasis on the size of the reservation period. We use a two‐stage Markov chain model to capture all possible events on the reservation and service periods. This allows the computation of the inflow and outflow of bandwidth requests (BWRs) and their associated data packets which leads to the delay and throughput formulas. By means of illustrative examples and numerical results, validated through simulation, we investigate the key importance of the size of reservation period. We highlight potential performance improvement, through opportunistic dynamic control of the size of the reservation period to enhance the performance of reservation MAC protocol. Copyright © 2008 John Wiley & Sons, Ltd.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.427

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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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