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Record W2146411427 · doi:10.1109/wcnc.2005.1424575

A clock-sampling mutual network time-synchronization algorithm for wireless ad hoc networks

2005· article· en· W2146411427 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
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceWireless ad hoc networkBeaconScalabilityComputer networkRobustness (evolution)Wireless sensor networkOverhead (engineering)Wireless networkClock synchronizationSynchronization (alternating current)Data synchronizationAlgorithmWirelessReal-time computingTelecommunications

Abstract

fetched live from OpenAlex

In this paper, we propose the clock-sampling mutual network synchronization (CSMNS) as a non-hierarchical and mutual network synchronization algorithm for wireless ad hoc networks. CSMNS shows superior performance to the IEEE 802.11 timing synchronization function in terms of accuracy, scalability and robustness. An overall view of the differences between the two approaches is presented. CSMNS is compatible with the beacon messages used in the IEEE 802.11 standard, and it is PHY transparent. CSMNS-RMN (rotating master node) is proposed in order to further reduce beacon collisions and overhead. Stability, is a factor that must be considered in CSMNS. However, values of the proportional gain below 0.3 suggest a good stability performance. The use of larger C/sup max/ values in more dense networks and/or the use of techniques that randomly prioritize the transmission of beacons can further reduce the overhead and risks of instability.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.802
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0010.001
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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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

Quick stats

Citations28
Published2005
Admission routes1
Has abstractyes

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