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Record W2403168237 · doi:10.21553/rev-jec.63

Geographic-based Routing in Smart Grid’s Neighbor Area Networks

2014· article· en· W2403168237 on OpenAlexafffund
Quang‐Dung Ho, Gowdemy Rajalingham, Tho Le‐Ngoc

Bibliographic record

VenueREV Journal on Electronics and Communications · 2014
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer networkComputer scienceGeographic routingSmart gridRouting protocolNetwork packetDynamic Source RoutingEngineering

Abstract

fetched live from OpenAlex

Neighbor area network (NAN), also known as smart meter communication network, is one of the most important segments of smart grid communications network (SGCN). This paper studies the performance of greedy perimeter stateless routing (GPSR), a representative implementation of geographic-based routing class, in the NAN scenario and investigates the feasibility of this routing protocol in supporting SG applications. Specifically, packet transmission delay and reliability of GPSR in an IEEE 802.15.4-based wireless mesh NAN with practical system parameters are measured by simulations. The results show that, at the data rate required for conventional SG applications including smart metering, real-time pricing and demand response, the delay can always be maintained below 70 ms (in 95th-percentile perspective) while packet delivery ratio is higher than 90%. However, due to that fact that more advanced applications that require information exchange at higher rates and more stringent delays are emerging in SG, the performance of GPSR in NAN scenarios using radio technologies that can support higher loads and/or larger network scales needs to be studied.

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.

How this classification was reachedexpand

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.433

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 integrity0.0000.001
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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2014
Admission routes2
Has abstractyes

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