TIHOO: An Enhanced Hybrid Routing Protocol in Vehicular Ad-hoc Networks
Why this work is in the frame
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Bibliographic record
Abstract
Recently, vehicular ad hoc network (VANET) is greatly considered by many service providers in urban environments. These networks can not only improve road safety and prevent accidents, but also provide a means of entertainment for passengers. However, according to recent studies, efficient routing has still remained as a big open issue in VANETs. In other words, broadcast storm can considerably degrade the routing performance. To address this problem, this research proposes TIHOO, an enhanced intelligent hybrid routing protocol based on improved fuzzy and cuckoo approaches to find the most stable path between a source and a destination node. In TIHOO, the route discovery phase is limited intelligently using the fuzzy logic system and, by limiting the route request messages, the imposed extra overhead can be efficiently controlled. Moreover, in figure of an intelligent hybrid approach, the improved cuckoo algorithm, which is one of the most effective meta-algorithms especially in the large search space, intelligently selects the most stable and optimal route among known routes by calculating an enhanced fitness function. The simulation results using NS2 tool demonstrate that TIHOO considerably improves network throughput, routing overhead, packet delivery ratio, packet loss ratio, and end-to-end delay compared to similar routing protocols.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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