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Record W2785313737 · doi:10.1109/pimrc.2017.8292229

A distance-based interest forwarding protocol for vehicular information-centric networks

2017· article· en· W2785313737 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
TopicCaching and Content Delivery
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceComputer networkNetwork packetBroadcast radiationVehicular ad hoc networkInformation-centric networkingProtocol (science)ForwarderRouting protocolWireless ad hoc networkWirelessTelecommunicationsCache

Abstract

fetched live from OpenAlex

Recently, information-centric networking has been proposed to VANETs scenarios for improving content delivery of infotainment applications. Using the ICN paradigm, content-oriented search and in-network caching have the potential to improve content delivery in spatial- and time-dependent applications for VANETs and smart transportation. However, uncontrolled Interest packet transmissions for content search will result in a waste of resources and diminish the performance of VANETs' applications. In this paper, we propose a lightweight protocol to tackle the Interest broadcast storm problem during a content search in information-centric VANETs. The proposed protocol considers the distance between a current forwarder and its neighboring vehicles to opportunistically control redundant Interest packet transmissions in vehicular named data networking. Simulation results show that the proposed protocol improves the content delivery rate by 60% while decreases the Interest packet transmissions by 40%, in the scenario of a low number of content producers in the network.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.960
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
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.043
GPT teacher head0.289
Teacher spread0.246 · 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

Citations36
Published2017
Admission routes1
Has abstractyes

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