A Hybrid Spatial Reuse MAC Protocol for Ad-Hoc Underwater Acoustic Communication Networks
Bibliographic record
Abstract
The most widely used medium access control (MAC) scheme for underwater acoustic communication (UWAC) networks is conventional time-division multiple access (TDMA), in which only a single node transmits at each time. Since this TDMA is the bottleneck in high traffic networks, in this paper we present a new MAC protocol for UWAC ad-hoc networks that applies spatial reuse to improve network throughput. More specifically, in the proposed protocol selected additional nodes can transmit simultaneously to the active TDMA node, thus improving the efficiency of the MAC protocol. By tracking the time-varying network topology, our protocol adaptively optimizes the set of active nodes and overcomes problems of UWAC networks such as the near-far problem, flickering, and formation of islands. We report performance results for both the conventional TDMA protocol and the proposed protocol from a sea trial at the Haifa harbor. The results show that the new protocol greatly increases the availability of nodes to transmit messages, which leads to an improved overall network throughput in high traffic networks.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".