LISIC: A Link Stability-Based Protocol for Vehicular Information-Centric Networks
Why this work is in the frame
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Bibliographic record
Abstract
Efficient content distribution is a critical challenge in vehicular networks (VANETs). This is due to the characteristics of vehicular networks, such as high mobility, dynamic topologies, short-lived links and intermittent connectivity between vehicles. Recently, information-centric networking (ICN) has been proposed to VANET scenarios for improving content delivery of infotainmentapplications. However, ICN in VANETs suffers from the Interest transmission broadcast problem, which results in a waste of resources and diminishes the performance of VANETs' applications. In this paper, we propose the link stability-based Interest forwarding for content request (LISIC) protocol, in order to tackle the Interest broadcast storm problem during a content search in information-centric VANETs. The proposed protocol controls Interesttransmission by prioritizing neighboring vehicles with more stable links with the current sender. Simulation results show that the proposed protocol improves the content delivery rate by 40% while decreases the Interest packet transmissions by 26%, in scenario of a low number of content producers in the network.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it