Voice over MPLS compared to voice over other packet transport technologies
Bibliographic record
Abstract
Most major carriers are deploying multiprotocol label switching (MPLS) and are also migrating voice traffic to packet transport. This article analyzes how those trends can be combined. It compares the advantages of VoMPLS with VoATM, VoIP, and VoFR, from the viewpoints of bandwidth utilization, implementation issues, and the region of the network (access/backbone) in which implementation takes place. VoMPLSoPPP is more efficient than VoMPLSoATM or VoMPLSoEthernet. In the network backbone VoMPLSoPPP is most efficient. VoAAAL2oATM has intermediate efficiency, and VoIP is highly inefficient. In the access network use of header compression improves the efficiency of VoIP but does not bring it to the level of VoAAL2oATM, which is approximately as efficient as VoMPLSoEthernet. VoMPLSoPPP remains most efficient.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".