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Record W2112133246 · doi:10.1109/ccnc.2009.4784804

Sip-Based Protocol for P2P Large-Scale Multiparty VoIP (MVoIP) Conference Support

2009· article· en· W2112133246 on OpenAlexaff
Wajdi Elleuch, Alain Houle

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsComputer scienceOverhead (engineering)Software deploymentVoice over IPProtocol (science)Computer networkDistributed computingProcess (computing)Control (management)Host (biology)Operating systemThe InternetArtificial intelligence

Abstract

fetched live from OpenAlex

Even if both traditional centralized and decentralized models can support small conferences, their deployment for large number of participants is less obvious. In fact, while server-based centralized conference facilitates control and administration operations, supporting centralized media processing in large scale conference causes system overhead on the mixer. On the other hand, decentralized solutions that use multi end-system media processors will introduce an overhead to control conference floors and users membership. Our solution introduces a new model that enable multi-host media process support while the conference control and management is kept simplified and centralized around the administrator. To do that, we build two different meshed networks to enable both voice audio distribution between participants and general conference control. Our conference system includes different components that enable conference creation/destruction, user addition/removal, media assignment and speech floor control. We introduce an abstract protocol message that implements membership operations. We also discuss the implementation of system components and we detail their mapping to SIP.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.412
Threshold uncertainty score0.975

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 communication0.0000.000
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 head0.040
GPT teacher head0.330
Teacher spread0.290 · 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 designNot applicable
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

Citations2
Published2009
Admission routes1
Has abstractyes

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