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Record W2149910782 · doi:10.1109/iccw.2010.5503950

A Hybrid Spatial Reuse MAC Protocol for Ad-Hoc Underwater Acoustic Communication Networks

2010· article· en· W2149910782 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer networkTime division multiple accessComputer scienceThroughputWireless ad hoc networkNode (physics)BottleneckProtocol (science)Distributed computingWirelessEngineeringTelecommunicationsEmbedded system

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.261
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it