An optimal management domain deployment scheme of Hierarchical AAA in mobile IPv6 networks
Bibliographic record
Abstract
In order to deal with the longer delay and extra cost arising from the combination of AAA (authentication, authority and accounting) and mobile Ipv6 fundamentally, a Hierarchical AAA Mobility Management (HAMM) architecture comprised of Root AAA Servers (RAAAS) and Leaf AAA Servers (LAAAS) is firstly constructed in this paper. HAMM will have much effective impact on reducing signaling cost and improving the management efficiency. Secondly, an algorithm is presented to set optimal size of management radius for RAAAS in terms of its mobility characteristics and some informed network parameters. Finally, the performance comparison demonstrates that the total cost of using HAMM is much lower than that of the best one of the existing solutions , the longer the distance between RAAAS and its home domain is, the more obvious the efficiency shows. By using this scheme, the system cost can be reduced to the minimum.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".