MétaCan
Menu
Back to cohort
Record W2138922897 · doi:10.1109/wcnc.2003.1200646

Modeling and analysis of WAP performance over wireless links

2004· article· en· W2138922897 on OpenAlex
Humphrey Rutagemwa, Xuemin Shen

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 Waterloo
Fundersnot available
KeywordsGoodputWireless Application ProtocolComputer scienceWirelessChannel (broadcasting)Rayleigh fadingComputer networkNetwork packetGeneral Packet Radio ServiceFadingWireless networkThroughputTelecommunications

Abstract

fetched live from OpenAlex

In this paper, an analytical model for studying the performance of wireless application protocol (WAP) over wireless links is proposed. A Rayleigh fading channel is used to characterize the behavior of wireless channel. Mathematical expressions which represent the performance of WAP as a function of the protocol and the channel parameters are derived. Computer simulation results are presented to validate the analytical results. It is shown that WAP performs better in a bursty error environment than in a random error environment. The goodput of WAP can be increased by increasing the WAP packet group size, but the significance of the improvement depends on the underlying channel condition.

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 score0.460
Threshold uncertainty score0.296

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 head0.201
Teacher spread0.195 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Wireless Network OptimizationFrench-language works237,207