Enhancing Path Stability Towards the Provision of Multimedia Support in Vehicular Ad Hoc Networks
Bibliographic record
Abstract
The recent advances and wide availability of wireless access technologies and inter-vehicle communication systems are expected to culminate in the integration of different wireless networks such as the IEEE 802.11, 3G/4G, and WiMax, multimedia and sensor networks in the next generation vehicular networks. However, due to high mobility of vehicles, several issues remain to be resolved before real-time multimedia based applications over VANETs become a reality. In this paper, we propose to study the provision of multimedia support in VANET, and present an efficient Path Stability Protocol, which we refer to as PASTA, as an additional module to MAC layer protocols that aims at preventing path breaks between vehicles that are frequently within reach of each other but not necessarily on a continuous basis. We discuss the implementation of our protocol, and report on its performance evaluation using a wide range of realistic scenarios. Our results indicate that our PASTA protocol decreases significantly the end-to-end latency as well as the network jitter.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".