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Record W2048767501 · doi:10.1002/dac.505

IP router architectures: an overview

2001· article· en· W2048767501 on OpenAlex

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

VenueInternational Journal of Communication Systems · 2001
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsComputer scienceRouterTerabitComputer networkNext-generation networkThroughputThe InternetCore routerInterconnectionIP forwardingTelecommunicationsRouting (electronic design automation)Routing protocolWorld Wide WebWirelessWavelength-division multiplexing

Abstract

fetched live from OpenAlex

Abstract In the emerging environment of high performance IP networks, it is expected that local and campus area backbones, enterprise networks, and internet service providers (ISPs) will use multigigabit and terabit networking technologies where IP routers will be used not only to interconnect backbone segments but also to act as points of attachments to high performance wide area links. Special attention must be given to new powerful architectures for routers in order to play that demanding role. In this paper, we identify important trends in router design and outline some design issues facing the next generation of routers. It is also observed that the achievement of high throughput IP routers is possible if the critical tasks are identified and special purpose modules are properly tailored to perform them. Copyright © 2001 John Wiley & Sons, Ltd.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.000
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 head0.064
GPT teacher head0.339
Teacher spread0.275 · 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