MétaCan
Menu
Back to cohort
Record W1621011156 · doi:10.1109/.2006.1629400

BGP with an Adaptive Minimal Route Advertisement Interval

2006· article· en· W1621011156 on OpenAlex
N. Laskovic, Ljiljana Trajković

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBorder Gateway ProtocolComputer scienceConvergence (economics)Computer networkInterval (graph theory)Default-free zoneInternetworkingThe InternetRouting protocolDistributed computingRouting (electronic design automation)MathematicsRouting tableOperating system

Abstract

fetched live from OpenAlex

The duration of the minimal route advertisement interval (MRAI) 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 paper, we propose the adaptive MRAI algorithm for adaptive adjustment of MRAI values. We also introduce reusable MRAI timers that independently limit advertisements of individual destinations. The modified BGP is named BGP with adaptive MRAI (BGP-AM). BGP processing delay used in the evaluation of BGP-AM is based on reported measurements, ns-2 simulation results demonstrate that BGP-AM leads to a shorter convergence time while maintaining a number of update messages comparable to the current BGP implementation. 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.

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: Methods · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.341

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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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

Quick stats

Citations15
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicNetwork Traffic and Congestion ControlFrench-language works237,207