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Record W1969614761 · doi:10.1002/nem.690

Limitations of current Ethernet switch architectures for enhanced flow control and service differentiation

2008· article· en· W1969614761 on OpenAlex
James Aweya, Delfin Y. Montuno, Michel Ouellette

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 Network Management · 2008
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsComputer scienceComputer networkCarrier EthernetEthernet flow controlFlow control (data)EthernetEthernet over SDHNetwork switch

Abstract

fetched live from OpenAlex

Abstract One of the new challenges associated with full‐duplex Ethernet is that of providing for network congestion control. The IEEE 802.3x Standard does not specify the switch architecture for implementing PAUSE flow control or at what point a MAC Control entity actually generates a PAUSE frame. This is an implementation issue that is product specific and as a result many different switch architectures are possible. There are also a number of limitations of the PAUSE flow control mechanism when implemented in Ethernet switches. These issues have not been adequately addressed in the literature. In addition, multimedia traffic such as real‐time voice and streaming video are now being deployed over switched Ethernet networks, thus calling for congestion control with service differentiation for the various classes of traffic. Here we examine current Ethernet switch architectures and show that the PAUSE flow control when implemented in these architectures does not provide service selectivity and differentiation, making it unsuitable for real‐time traffic. Copyright © 2008 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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.933
Threshold uncertainty score0.367

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 science0.0010.000
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 head0.038
GPT teacher head0.257
Teacher spread0.219 · 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