Performance Evaluation of Topology based Routing Protocols in a VANET Highway Scenario
Bibliographic record
Abstract
Vehicular Ad-Hoc Network (VANET) has been derived from the well-established Mobile Ad-hoc Network (MANET). It facilitates wireless communication among vehicles to roadside equipment. Such kind of communication is utilized for different purposes such as safety, comfort, or even entertainment. The performance of VANET applications are highly determined by its underlying routing protocols. In this paper, the authors investigate the performance of topology based MANET routing protocols (AODV, DSDV and DSR) in a VANET highway design using NCTUNS 6.0 simulator. Different parameters are varied including speed, node density, propagation loss model, fading effects, data rate and payload. The selected routing protocols are then evaluated in terms of performance metrics throughput, packet drop and packet collision. Results shows that the performance of routing protocols depends on the application requirements in terms of throughput, delay and percentage of packet drops.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".