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Record W1915092061 · doi:10.1155/2015/307031

Effective Transmission Coverage Area-Based Link Dynamics Characterization of VANET in Highway Scenario

2015· article· en· W1915092061 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

VenueInternational Journal of Distributed Sensor Networks · 2015
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsUniversity of Ottawa
FundersNational Natural Science Foundation of China
KeywordsComputer scienceLink (geometry)Queueing theoryVehicular ad hoc networkTransmission (telecommunications)Routing (electronic design automation)Link budgetMobility modelComputer networkTelecommunicationsWirelessWireless ad hoc network

Abstract

fetched live from OpenAlex

This paper uses the concept of effective transmission coverage area as a model for the derivation of analytic expressions in order to characterize the dynamic statistics of link lifetime, new link arrival rate, new link interarrival time, link breakage interarrival time, and so forth. Extensive simulations have been undertaken to verify the derived analytical expressions via generated mobility traces. Results demonstrate that the proposed analytical model can characterize the dynamic statistics well. Furthermore, the mathematical results of expected link life and expected new link arrival rate are provided to be used in analyzing the network connectivity. Combining with queueing theory, the upper bound connectivity of a VANET is obtained. This work thus provides a fundamental guideline on designing new mobility models, new routing protocols, and the corresponding performance analysis in VANET.

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: Empirical · Consensus signal: none
Teacher disagreement score0.587
Threshold uncertainty score0.882

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 head0.007
GPT teacher head0.209
Teacher spread0.202 · 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