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Record W2167258973 · doi:10.1109/jsac.2007.070614

Load-Balancing Data Traffic Among Inter-Domain Links

2007· article· en· W2167258973 on OpenAlexaff
Mohamed El-Darieby, Dorina C. Petriu, Jerry Rolia

Bibliographic record

VenueIEEE Journal on Selected Areas in Communications · 2007
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsCarleton UniversityUniversity of Regina
Fundersnot available
KeywordsComputer scienceComputer networkThe InternetInternet transitInternet backboneNetwork congestionInternet traffic engineeringService (business)Bandwidth (computing)Internet trafficNetwork traffic controlInter-domainInternet exchange pointWorld Wide WebMulticast

Abstract

fetched live from OpenAlex

The Internet has evolved into a multi-service infrastructure for the telecom and computer industries. Internet services are affected by congestions caused by the operations of Internet routing protocols. We propose a novel information service that guides the operations of Internet routing protocols to avoid such congestion. The information service maintains information about utilization of inter-domain links. The proposed service minimizes the maximum of utilization of Internet links by selecting potential network domains to be traversed by Internet services. Simulation results show better balanced distribution of traffic workloads among network links using the proposed service. We show that the proposed service scales well as network size grows. This comes at the cost of greater control messaging overhead which suggests using the proposed service with long-lived and higher bandwidth services

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)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.034
GPT teacher head0.296
Teacher spread0.262 · 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
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

Citations7
Published2007
Admission routes1
Has abstractyes

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