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Record W1969460318 · doi:10.1109/sarnof.2008.4520089

Multipath routing with adaptive playback scheduling for Voice over IP in Service Overlay Networks

2008· article· en· W1969460318 on OpenAlexafffund
Hong Li, L.G. Mason

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVoice over IPComputer scienceComputer networkQuality of serviceScheduling (production processes)Multipath propagationJitterPhoneHandoverTelecommunicationsThe InternetEngineering

Abstract

fetched live from OpenAlex

Voice over IP (VoIP) quality of service provision over the best effort Internet remains a challenging task since an interactive level conversation has strict delay, loss and delay jitter requirements. The ITU-T E-model [1] defines R-factor to measure the subjective quality of VoIP phone calls. Multipath routing and adaptive playback scheduling have been proposed to improve the quality of VoIP phone calls. However, it is still not clear how to select a multipath at the sender so that the best quality is achieved for voice signals. We propose a novel mechanism to select the optimal multipath that provides the best R-factor for VoIP phone calls with adaptive playback scheduling being applied at the receiver. We evaluate the VoIP quality for the proposed mechanism by comparing the R-factor of the VoIP calls sent through the optimal multipath with that of the VoIP calls sent through the direct path (the shortest hop path decided by the underlying network). The results show that the proposed method can raise the VoIP quality and provide much more stable quality for VoIP calls.

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 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 score0.817
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.223
Teacher spread0.202 · 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 teacher head, not a consensus.

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

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

Citations6
Published2008
Admission routes2
Has abstractyes

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