Multicast Forwarding Using Multiple Gateways and Hash for Duplicate Packet Detection in a Tactical MANET
Bibliographic record
Abstract
Simplified Multicast Forwarding (SMF) [3] provides an optimized flooding mechanism in MANET environments to efficiently propagate multicast packets. In order to be more useful in a broader range of scenarios, we need to be able to get multicast packets to and from fixed infrastructures. Gateways in MANETs are more complex than regular MANET nodes as they require both to join multicast groups on behalf of the MANET, as well as to forward multicast packets between networks. Multicast gateways are required to interoperate with other multicast routing protocols in the wired domain. In this paper we show that by using a hash function we are able to assign packets with a common unique packet identifier that is further used for duplicate packet detection. Using the hash function in conjunction with multiple gateways, we lower the traffic overhead, increase the packet delivery ratio, and make the protocol more resilient to network partitioning as well as independent to the number of gateways.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".