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Record W2099766752 · doi:10.1109/ccece.2005.1556918

The adoption of dynamic weight mapping function in adaptive routing

2006· article· en· W2099766752 on OpenAlexaff
M.R. Ito

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAdaptive routingComputer scienceDynamic Source RoutingRouting (electronic design automation)Routing protocolStatic routingLink-state routing protocolStability (learning theory)Path vector protocolZone Routing ProtocolEnhanced Interior Gateway Routing ProtocolFunction (biology)Wireless Routing ProtocolDistance-vector routing protocolDistributed computingComputer networkMachine learning

Abstract

fetched live from OpenAlex

A dynamic weight mapping adaptive routing algorithm (DWMAR) is proposed in this paper to provide an optimized and stable adaptive routing protocol. The online dynamic weight mapping function is customized for each link. DWMAR adopts different adaptive policies on different link loads to make up for the unstable nature of adaptive routing. The performance of DWMAR is tested in simulations. The results are compared to the non-adaptive SPF algorithm and the load sensitive adaptive routing (LSAR) algorithm. DWMAR shows improved performance in terms of network efficiency and stability.

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)0.003
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.184
Teacher spread0.177 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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