Bibliographic record
Abstract
We propose and present a framework for enabling policy-based routing in mobile ad hoc networks (MANETs) by applying policy rules associated with the security and reliability (of connection) to peer-to-peer security associations (SA) that are established on (multi-link) routes. In this proposal, we leverage and integrate the concept of dispersity routing with the management and maintenance of an existing modular security architecture. We adopt the Ad hoc On-demand Multipath Distance Vector (AOMDV) routing protocol to achieve dispersity routing. We further expand the modular security architecture, containing the Trust-enhanced Routing Table (TRT) module to include a reliability metric so that a route, among multiple available routes to a destination, may be selected and tracked with policy-set parameters. Under our proposal, a secure route is one that would be mapped through authenticated (trusted) nodes with established SAs, whereas a reliable route is one that would have a high Mean Time Between Failures (MTBF). The combination of trust and reliability as parameters used with multiple routes renders a graded routing service - the capability of providing several potential routes to a destination in a MANET, each of which may be selected because its security and reliability metrics match those of the policy. We support this proposal with a proof of concept simulation and we discuss that secure and reliable policy-based routing in MANETs is a worthwhile area for further research and investment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".