Multicasting in ad-hoc networks: Comparing maodv and odmrp
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. Multicasting can efficiently support a variety of applications that are characterized by a close degree of collaboration, typical for many ad-hoc applications currently envisioned. Within the wired network, well-established routing protocols exist to offer an efficient multicasting service. As nodes become increasingly mobile, these protocols need to evolve to similarly provide an efficient service in the new environment. This paper discusses the performance of two proposed multicast protocols for ad-hoc networks: MAODV and ODMRP. MAODV builds and maintains a multicast tree based on hard state information, ODMRP maintains a mesh based on softstate. Our results show that in many scenarios ODMRP achieves a higher packet delivery ratio, but results in much higher overheads.
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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) | 0.001 | 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 it