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Record W2105636780 · doi:10.1109/iscc.2000.860623

Design and performance of a scalable real time control protocol: simulations and evaluations

2002· article· en· W2105636780 on OpenAlexaff
Randa El-Marakby

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsRTP Control ProtocolComputer scienceScalabilityComputer networkProtocol (science)MulticastQuality of serviceDistributed computingReal-time computingOperating systemNetwork packet

Abstract

fetched live from OpenAlex

Scalability problems which arise when the real time control protocol (RTCP) is used in large multicast groups include: increased feedback delay, increased storage state at every member; and ineffective RTCP bandwidth usage. This paper presents a scalable RTCP (S-RTCP). S-RTCP is based on a hierarchical structure in which members are grouped into local regions. For every region, there is an aggregator (AG) which receives the feedback receiver reports (RRs) of the local members, summarizes important information in the RRs, derives some statistics, and sends them to a manager. The manager performs additional statistical analysis to monitor the transmission quality and to identify regions of high congestion. A simulation of S-RTCP using the network simulator (NS) shows that S-RTCP alleviates some of RTCP scalability problems. Consequently, the feedback provides timely and useful QoS information required for network monitors and for adaptive applications. The main contribution of this paper is the presentation of the simulations' details and performance analysis that show the advantages of using S-RTCP over the original RTCP.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.237

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 head0.023
GPT teacher head0.257
Teacher spread0.234 · 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
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

Citations6
Published2002
Admission routes1
Has abstractyes

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