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Record W7055033322

BGP with an adaptive minimal route advertisement interval

2006· dissertation· en· W7055033322 on OpenAlexfundno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2006
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAdvanced Frequency and Time Standards
Canadian institutionsnot available
FundersSimon Fraser University
KeywordsBorder Gateway ProtocolConvergence (economics)Interval (graph theory)Network topologyDuration (music)Protocol (science)Limit (mathematics)Retard
DOInot available

Abstract

fetched live from OpenAlex

The duration of the Minimal Route Advertisement Interval (MRA.1) and the implementation of MRAI timers have a significant influence on the convergence time of the Border Gateway Protocol (BGP). Previous studies have reported existence: of optimal MRAI values that minimize the BGP convergence time for various network topologies and traffic loads. In this thesis, we propose the adaptive MRAI algorithm for adaptive adjustment of MRAI values. We also introduce reusable MRAI timers that limit the number of advertisements for each destination.. The modified BGP is namedl BGP with adaptive MRAI (BGP-AM). BGP-AM perfimnance is evaluated using the BGP processing delay based on reported measurements. ns-2 simulation results d-emonstrate that BGP-AM leads to a shorter convergence time and a number of update messages comparable to the current BGP. Furthermore, BGP-AM convergence time depends linearly on the BGP processing delay.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.008
GPT teacher head0.220
Teacher spread0.213 · 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
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

Citations1
Published2006
Admission routes1
Has abstractyes

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