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Record W2111722589 · doi:10.1109/glocom.1989.64115

An analytical technique for evaluating packet routing policies in metropolitan area networks

2003· article· en· W2111722589 on OpenAlexaff
Bhumip Khasnabish

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsMcMaster University
Fundersnot available
KeywordsComputer scienceTopology (electrical circuits)Network packetIdeal (ethics)Network topologyUpper and lower boundsComputer networkRouting (electronic design automation)Metropolitan area networkMathematicsLocal area network

Abstract

fetched live from OpenAlex

An analytical technique for evaluating packet routing strategies in metropolitan (or wide) area networks is presented. This technique determines the upper bound of the mean packet transfer time in a class of regular mesh networks called Manhattan street networks. The proposed technique is based on determining the internode distance distribution and the topology z-transform for an ideal (i.e. where the links are of infinite capacity or the nodes are equipped with infinite buffer space) version of the network under consideration for a specific traffic distribution pattern. Deviations from the ideal conditions are taken into account by incorporating a tuning parameter and a penalty indicator in the performance equations. The value of the tuning parameter is zero for the ideal network. The penalty indicator depends on the network's topology and the type (i.e. half-duplex or full-duplex) of communication links used in the network.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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)0.002
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 score0.981
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.043
GPT teacher head0.334
Teacher spread0.291 · 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
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

Citations8
Published2003
Admission routes1
Has abstractyes

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