Modeling the Throughput and Delay in Wireless Multihop Ad Hoc Networks
Why this work is in the frame
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Bibliographic record
Abstract
In wireless multihop ad hoc networks, the use of the RTS/CTS mechanism does not completely eliminate the hidden-terminal problem. Considering the hidden-terminal problem adds complexity to the existing analysis for single-hop networks. In this paper, we provide precise and accurate analytical models for quantifying the throughput and delay in wireless multihop ad hoc networks. The proposed analysis is applicable to many wireless MAC protocols and applications. The accuracy of our analytical models are verified by extensive NS-2 simulations. Our analysis reveals how the throughput and delay in wireless multihop ad hoc networks are affected by the hidden-terminals and by the transmission and interference ranges of wireless devices. These results are important for network planning and protocol optimization in wireless multihop ad hoc networks.
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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 | 0.001 | 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 it