Architecture and Performance Analysis of the Multicast Balanced Gamma Switch for Broadband Communications1
Bibliographic record
Abstract
Abstract — This paper presents the architecture design as well as the performance analysis of a new cell-based multicast switch for broadband communications. Using distributed control and a modular design, the Balanced Gamma (BG) switch features a high performance for unicast, multicast and combined traffic under both random and bursty conditions. Although it has buffers on input and output ports, the multicast BG switch follows predominantly an output-buffered architecture. The performance is studied under uniform and non-uniform multicast traffic in terms of cell loss ratio and cell delay. The results are compared with those from an ideal pure output-buffered multicast switch to demonstrate how close its performance is to that of the ideal but impractical switch. Comparisons with other published switches reveals the superior of the BG switch and the tradeoffs between complexity and performance in a packet switch design. It is shown that the multicast BG switch achieves a performance close to the ideal switch while keeping hardware complexity reasonable. Index Terms — Multicast, Balanced Gamma (BG) switch, performance analysis, multistage interconnection network (MIN),
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".