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Record W2089985602 · doi:10.1504/ijmc.2009.023694

A reliable communications architecture for real-time IP mobile applications

2009· article· en· W2089985602 on OpenAlexaff
J-Ch. Gregoire, Omneya Issa, Yacine Belala, James Wong

Bibliographic record

VenueInternational Journal of Mobile Communications · 2009
Typearticle
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsSystems, Applications & Products in Data Processing (Canada)Communications Research Centre CanadaInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsComputer scienceQuality of serviceComputer networkReliability (semiconductor)WirelessArchitectureAdaptation (eye)Distributed computingTelecommunications

Abstract

fetched live from OpenAlex

While the availability of a variety of wireless access technologies already provides users with ubiquitous access to critical content and applications, ensuring a satisfactory Quality of Service (QoS) and high availability further requires reliable delivery schemes that optimally use the available bandwidth. This paper presents a novel architecture to support adaptive real-time IP applications. It includes a layer of abstraction to isolate the application from the actual transport channels. It also uses a message-based protocol to improve communications reliability. Adaptation mechanisms are introduced and validated using a healthcare application. Experimental results are reported that demonstrate the viability of the approach.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.292
Teacher spread0.279 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2009
Admission routes1
Has abstractyes

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