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Record W2941684496 · doi:10.1109/jsen.2019.2912938

Prioritized Clock Synchronization for Event Critical Applications in Wireless IoT Networks

2019· article· en· W2941684496 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Sensors Journal · 2019
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceComputer networkWireless sensor networkQuality of serviceNetwork packetWireless networkWirelessKey distribution in wireless sensor networksSynchronization (alternating current)Distributed computingScheduling (production processes)Access controlMedia access controlChannel (broadcasting)TelecommunicationsEngineering

Abstract

fetched live from OpenAlex

With the proliferation of the Internet of Thing (IoT) technologies in vertical industry applications, provisioning of accurate synchronization and low latency communication has become critical for dense wireless IoT networks to support distributed sensing and control. Due to the contention-based channel access, achieving accurate synchronization in most of unlicensed wireless IoT networks could be extremely challenging. Specifically, the critical challenge at medium access control (MAC) layer for dense IoT communication is how to eliminate random access delay while supporting a large number of heterogeneous nodes with diverse quality of service (QoS) requirements. In this paper, we propose an efficient MAC protocol for supporting distributed synchronization through guaranteed channel access for time-critical sensor nodes in dense wireless IoT networks. The proposed protocol assigns time slots to timestamp packets of the time-critical nodes using a prioritized channel access mechanism, and also guarantees channel access in event-based situations. In addition, the proposed protocol also provides deterministic scheduling for the scenarios where the delay bound of a certain priority traffic changes based on the circumstances of the emergency situation. Our results show that the proposed scheme significantly improves the synchronization precision of the event critical sensor nodes, and also enhances the reliability of overall IoT 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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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