Using an IEEE 802.1AS network as a distributed IEEE 1588 boundary, ordinary, or transparent clock
Bibliographic record
Abstract
IEEE 802.1AS includes a very specific profile of IEEE 1588 that only runs at layer 2 over networks that follow the IEEE 802 architecture. It has some significant performance and scalability advantages, but at the cost of not allowing non-PTP-aware devices. This paper describes how a network having a common source of time can act as a distributed IEEE 1588 boundary, ordinary, or transparent clock, allowing the network to transport synchronization between portions of an IEEE 1588 network domain, and do this for any number of domains simultaneously. The network that acts as a distributed clock can be a PTP network supporting a profile that is different from that of the domains whose timing it is transporting. As one example, an IEEE 802.1AS network can act as a distributed IEEE 1588 boundary, ordinary, or transparent clock. As part of the discussion, the paper also shows that an IEEE 1588 boundary clock and peer-to-peer transparent clock are functionally equivalent in the manner in which they transport synchronization, and that the principal difference between the two is that the former invokes a best master clock algorithm (either default or alternate) and implements the full PTP state machine, while the latter does not. The concepts of distributed BC, TC, and OC, and the equivalence of the BC and peer-to-peer TC may be considered a new way of looking at the transport of synchronization in a network based on IEEE 1588.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".