Competitive Wireless Access for Data Streaming over Vehicle-to-Roadside Communications
Why this work is in the frame
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Bibliographic record
Abstract
This paper considers the problem of optimal and competitive wireless access for data streaming over vehicle-to-roadside (V2R) communication. In a service area, the onboard units (OBUs) in vehicles use wireless access to download streaming data from the roadside units (RSUs). The downloaded streaming data can be stored in proxy buffer for the application to playout. The wireless access can be in reservation or on-demand mode. While the price of wireless access in reservation mode is fixed, that of on-demand mode is determined from the total demand from all OBUs. The OBUs compete with each other for wireless access to a particular RSU. The objective of an OBU is to minimize the cost for wireless access while the quality-of-service (QoS) requirement (e.g., buffer underrun probability) of the streaming application is met. A stochastic game is formulated to model this competitive situation in which OBUs are the players of this game. The strategy of an OBU is the wireless access policy (i.e., the amount of bandwidth to be used for downloading streaming data). The constrained Nash equilibrium is considered to be the solution of this stochastic game. This solution ensures that the cost of each OBU is minimized given the wireless access policies of other OBUs and thus none of the OBUs would unilaterally change its policy for wireless access. In addition, the solution guarantees that the QoS requirement of streaming application is met.
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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 | 0.001 |
| Open science | 0.001 | 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