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Record W2889409284 · doi:10.1109/iwcmc.2018.8450523

Energy Efficiency Analysis of Centralized-Synchronous LoRa-based MAC Protocols

2018· article· en· W2889409284 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
TopicIoT Networks and Protocols
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceComputer networkEfficient energy useEmbedded systemElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

LoRa is a PHY layer technology that has been gaining popularity with IoT platfrom developers, due to its low-power long-range communication. As a result, different classes of LoRabased MAC layer protocols have been proposed, with the key ones being either contention-based or centralized-synchronous. Since most of the research literature focused on analyzing the efficiency of contention-based LoRa protocols, we sought to study the efficiency of centralized-synchronous protocols. We utilized a tailored simulator to analyze the energy efficiency of LoRa-based centralized-synchronous protocols. Our findings, are backed up by hardware performance measurements. After comparing the energy efficiency of the centralized-synchronous protocols against that of other LoRa-based MAC layer protocol classes, we found that the lifetime of a device using a centralized-synchronous protocol was up to four times longer than that of a contentionbased device. These findings, as well as our insights, will aid the development of future energy-efficient LoRa-based MAC protocols.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.261
Teacher spread0.250 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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