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Record W2063978548 · doi:10.1002/nem.505

Circuit emulation services over Ethernet—Part 1: Clock synchronization using timestamps

2004· article· en· W2063978548 on OpenAlexaff
James Aweya, Michel Ouellette, Delfin Y. Montuno, Kent Felske

Bibliographic record

VenueInternational Journal of Network Management · 2004
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsMetro EthernetComputer scienceComputer networkEthernet over PDHSynchronous EthernetCarrier EthernetEthernetClock synchronizationEthernet over SDHConnection-oriented EthernetEthernet flow controlSynchronization (alternating current)Embedded systemTelecommunications

Abstract

fetched live from OpenAlex

Abstract Due to Ethernet's ubiquity, simplicity, scalability and cost effectiveness there is significant customer demand for Ethernet‐based access and transport in the metropolitan network. Many service providers have recognized this need and are currently establishing Ethernet‐based services to meet this demand. The migration to all‐Ethernet access will not be instantaneous since many customers currently have legacy TDM access interfaces on their routers and PBX equipment. Circuit Emulation Services (CES) over Ethernet provides TDM circuit emulation to support TDM traffic such as T1/E1, T3/E3, OC3/12, etc. This two‐part paper presents the application of CES over Ethernet as well as a new technology that addresses the issues associated with clock recovery and synchronization in an Ethernet network with its inherent network jitter. Part 1 describes a clock synchronization technique where a transmitter periodically sends explicit time indications or timestamps to a receiver to enable the receiver to synchronize its local clock to the transmitter's clock. Copyright © 2004 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.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.012
GPT teacher head0.250
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreEmpirical

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

Citations23
Published2004
Admission routes1
Has abstractyes

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