Scheduling algorithm based on preemptive priority and hybrid data structure for cognitive radio technology with vehicular <i>ad hoc</i> network
Why this work is in the frame
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Bibliographic record
Abstract
There are different types of messages containing different priorities in vehicular ad hoc networks. Hence, queue rescheduling is required according to priorities of arrived messages. In this study, a data structure with less computational complexity is proposed to minimise queuing delay. Further, to maintain quality of service, preemptive priority is applied to time‐bound safety messages by transferring non‐safety messages to other bands using the concept of cognitive radio technology. The time‐bound messages are transmitted using the dedicated short‐range communication spectrum without the need for spectrum sensing by vehicles. The other messages with no deadline constraint are switched to other bands near‐dedicated short‐range communication spectrum. The results show that 6.25% improvement in packet delivery ratio of cognitive radio‐enabled preemptive priority is achieved in comparison to existing cognitive radio protocol. The delay shows a slight increment of 1.1%. The packet delivery ratio of cognitive radio‐enabled non‐preemptive priority is improved by 3.24% while the delay is improved by 3.17%. The data storage required for storing sensing data of 50 channels for 10 days is only 45 Mb.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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