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Record W2291125951 · doi:10.1109/glocom.2015.7417599

A Performance Study of CPRI over Ethernet with IEEE 802.1Qbu and 802.1Qbv Enhancements

2015· article· en· W2291125951 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

Venue2015 IEEE Global Communications Conference (GLOBECOM) · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsHuawei Technologies (Canada)
Fundersnot available
KeywordsJitterEthernetEthernet flow controlComputer networkComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

There has been a debate on whether or not Ethernet, a highly cost effective technology, could meet the stringent latency and jitter requirements imposed by CPRI. To facilitate the discussion, we conducted simulations to understand how Ethernet performs when carrying CPRI traffic with the two Ethernet enhancements, currently being standardized by IEEE, namely frame preemption (802.1Qbu) and scheduled traffic (802.1Qbv). Our simulation results led to two conclusions: 1) Ethernet networks with or without frame preemption, regardless of being shared or dedicated to CPRI traffic, can not meet the CPRI jitter requirement of 8:138 ns, confirming a widely hold belief; 2) Ethernet with the enhancement of scheduled traffic in conjunction with a well defined scheduling algorithm could significantly lower or even completely remove jitter thus could meet CPRI jitter requirement. To the best of our knowledge, this paper is among the first to study the performance of Ethernet with IEEE 802.1Qbu and 802.1Qbv enhancements and to demonstrate by simulation that Ethernet with scheduled traffic could meet CPRI jitter requirement.

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 categoriesMeta-epidemiology (narrow)
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 score0.678
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.058
GPT teacher head0.303
Teacher spread0.245 · 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