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Record W2567191584 · doi:10.1109/cisis.2016.110

A Reliable and Interference-Aware Routing Protocol for Underwater Wireless Sensor Networks

2016· article· en· W2567191584 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 AlbertaDalhousie University
Fundersnot available
KeywordsComputer networkComputer scienceRouting protocolGeographic routingForwarderDynamic Source RoutingNetwork packetWireless Routing ProtocolZone Routing ProtocolSource routingWireless sensor networkEqual-cost multi-path routingPath vector protocol

Abstract

fetched live from OpenAlex

In this paper, we propose a reliable and interference-aware routing protocol for underwater wireless sensor networks (UWSNs). Proposed protocol follows end-to-end path from source node to sink and selects next forwarder node of a data packet on the basis, having already established a path to sink. In this way, the problem of encounters void hole in depth based routing protocol is eliminated. Furthermore, during the selection of forwarding node, channel interference is also considered as routing metric to provide reliable communication. Therefore, proposed scheme reduces the probability of collision at the network layer, by selecting a neighbor node as the next forwarder of the data packet from the source node to the destination where the chance of channel interference is minimum. Simulation results verify the effectiveness of the proposed scheme in term of energy consumption, end-to-end delay and packet delivery ratio especially in a sparse network.

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 score0.963
Threshold uncertainty score0.280

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 science0.0000.000
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 head0.032
GPT teacher head0.257
Teacher spread0.226 · 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