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Record W2121320520 · doi:10.1002/sec.134

Performance analysis of secure on‐demand services for wireless vehicular networks

2009· article· en· W2121320520 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

VenueSecurity and Communication Networks · 2009
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsComputer scienceComputer networkScalabilityLatency (audio)Software deploymentWirelessService (business)Computer securityTelecommunications

Abstract

fetched live from OpenAlex

Abstract Wireless vehicular communications pose significant challenges for the deployment of next generation roadside services. Some important issues that must be tackled are security, billing, and reliability while guarantying a scalable service delivery. This paper addresses the assignation of secure service session parameters upon the reception of on‐demand service requests by an incumbent services district domain and studies and analyses the performance of the underlying mechanisms. Three types of service request protocols are introduced in our work defined as single‐hop (SHI‐RQ), extended connectivity (EC‐RQ), and multi‐hop (MHI‐RQ) service requests. A detailed analytical model and cost study for the access protocols are presented. Our analysis study covers the estimation of total cost in terms of latency for each access protocol with different mobility characteristics and vehicle densities within the service coverage area and across different serving district domains. The analytical results are consistent with the experimental one and show that the access protocols cost in terms latency remains acceptable for a realistic number of serviced vehicles even at high speeds. Copyright © 2009 John Wiley & Sons, Ltd.

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)0.001
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 score0.508
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.007
GPT teacher head0.228
Teacher spread0.222 · 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