Reducing Handoff Latency for NEMO-Based Vehicular Ad Hoc Networks
Why this work is in the frame
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Bibliographic record
Abstract
In a vehicular ad hoc network, vehicles can communicate with their correspondent nodes through the Internet using various wireless technologies. This kind of wireless networks brings a lot of new applications to metropolitan networks, such as online games, VoIP, etc. However, compared with traditional wireless networks, the high speed of vehicles and the limited transmission range of antennas introduce more frequent handoffs. During the handoff, vehicles have to switch their access points to establish new connections and the current wireless communications will be ceased temporarily. Therefore, long handoff latency causes poor throughput and obvious jitter. In this paper, a fast handoff scheme is proposed for vehicular networks. Using this scheme, vehicles are divided into different clusters; and within each cluster, the network mobility solution is used to reduce the total number of handoffs. Moreover, before the mobile routers start actual handoff process, they can receive their new care of addresses through assistant nodes in the same cluster. Simulation results demonstrate that handoff latency can be significantly reduced by our scheme.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 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