Mechanisms for Multi-Packet Reception Protocols in Multi-Hop Networks
Bibliographic record
Abstract
We consider multi-hop wireless networks composed of nodes with transceivers capable of multi-packet transmission and reception (MPT/MPR). Legacy MAC protocols based on CSMA/CA are overly restrictive in the interest of avoiding collisions, and are unable to exploit the MPR capability of receivers. We demonstrate how a combination of mechanisms, based on well-known techniques, such as Additive Increase Multiplicative Decrease (AIMD), and the back--pressure (BP) principle, can be used to effectively control medium access in multi-hop MPT/MPR networks. The AIMD component is used to regulate the size of "bundles" of simultaneously transmitted packets, while back--pressure provides the basis for prioritizing, locally, which flows' packets should be transmitted in a bundle. We study the performance of the proposed protocol, AB-MAC, under three different models of node coordination in static wireless multi-hop MPT/MPR networks. We find that, under various scenarios and for the same capacity resources, AB-MAC's throughput performance surpasses that of IEEE 802.11b.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".