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Record W1958608222 · doi:10.1109/wcnc.1999.796933

Service scheduling for general packet radio service classes

2003· article· en· W1958608222 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsMotorola (Canada)University of British Columbia
Fundersnot available
KeywordsGeneral Packet Radio ServiceComputer networkComputer scienceQuality of serviceBottleneckScheduling (production processes)GPRS core networkAccess Point NameNetwork packetFIFO (computing and electronics)Real-time computingTelecommunicationsWirelessEngineeringOperating systemEmbedded system

Abstract

fetched live from OpenAlex

While the quality of service (QoS) profiles for a number of general packet radio service (GPRS) classes has been specified by ETSI, how QoS management is provided by means of traffic scheduling, traffic shaping, and connection admission control, in a GPRS network is an implementation issue that is attracting significant current research interest. This paper presents an evaluation of several traffic scheduling methods, including of FIFO, static priority scheduling (SPS) and earliest deadline first (EDF) by simulations, with the objective of meeting the delay profiles defined for a number of GPRS classes. Traffic sources representative of GPRS applications, including e-mail, fleet management and World Wide Web applications are employed. We focus on the forward link which represents the bottleneck of a typical GPRS data connection. Results show that EDF is able to meet the delay requirements at a much higher channel utilization compared to the other alternatives.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.952
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.059
GPT teacher head0.319
Teacher spread0.260 · 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

Citations46
Published2003
Admission routes1
Has abstractyes

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