A broadband integrated services network architecture based on DWDM
Bibliographic record
Abstract
The broadband integrated service network (B-ISDN) had been considered as one of the leading network architectures of fiber to the home for delivering integrated services for a quite long period of time. However, with the development of the dense wavelength division multiplexing (DWDM) technology, large number of channels of lights with different wavelengths are used to transmit data within one single fiber. This increases the bandwidth capacity of a single fiber by tens or even hundreds of times. DWDM has been deployed for long-haul transmissions and will surely change the landscape of fiber-to-the-home network architecture and protocols. Utilizing the bandwidth capability of DWDM to deliver broadband integrated services to homes is an important area of research. This paper presents a virtual star network architecture based on the very high channel count DWDM (VHCC-DWDM) framework, which uses the wavelength channels within one fiber to link the users with the service providers or the edge routers of the Internet. The paper discusses the network architectural issues, which include the network topology, the very high channel count DWDM, the wideband-low-loss fiber for access networks, and the user premises. The paper starts with an overview of the DWDM based residential access networks which have been developed in the literature.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".