Multicast Transport Protocols for Large‐Scale Distributed Collaborative Environments
Bibliographic record
Abstract
This chapter provides an overview of multicast transport protocols. It also provides an introduction to multicasting and the features that can be added to satisfy each application's requirements. The chapter describes multicast protocols by classifying them according to several features. As the number of applications using multicasting has grown, the number of multicast transport protocols has increased as well. The latter can be classified into three categories, depending on the type of applications: general-purpose protocols such as reliable broadcast protocol (RBP), multicast transport protocol (MTP), reliable multicast protocol (RMP), and Xpress transport protocol (XTP); multicast interactive applications such as multicast transport protocol-2 (MTP-2), real-time transport protocol (RTP), scalable reliable multicast (SRM), and reliable adaptive multicast protocol (RAMP); and data distribution services such as tree-based multicast transport protocol (TMTP), reliable multicast transport protocol (RMTP), multicast file transfer protocol (MFTP), and tree-based reliable multicast protocol (TRAM).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".