Implementation of a kernel mode IPv6 AODV routing daemon to improve data throughput
Bibliographic record
Abstract
The AODV (ad hoc on-demand distance vector) routing protocol performs on-demand route discovery that minimizes the signaling overhead on the wireless channel at the expense of larger session setup delays. While large delays may be acceptable at session set up, they are certainly undesirable during handoffs when the session is already in progress. Our previous work addressed the problem of session handover delay within an ad hoc network connected to the Internet at large via IPv6 MANET gateways. This paper presents an extension of that earlier work by addressing another shortcoming of the AODV routing protocol - the often high overhead involved in maintaining (refreshing) active routes incurred by the active monitoring of a user-mode AODV routing daemon. A Linux kernel-based port of the AODV6 routing daemon and gateway component was developed to minimize the demands placed upon the individual mobile node's processing capabilities. A real test-bed is implemented and performance benchmarks are presented to demonstrate the viability of the proposed architecture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".