Tag-assisted social-aware opportunistic device-to-device sharing for traffic offloading in mobile social networks
Why this work is in the frame
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Bibliographic record
Abstract
In recent years, the service demand for rich multimedia over mobile networks has continually been soaring at a tremendous pace. To solve the critical problem of mobile traffic explosion, substantial efforts have been made by researchers to try to offload mobile traffic from infrastructured cellular links to direct short-range communications locally among nearby users. In this article, we discuss the potential of combining users' online and offline social impacts to exploit D2D opportunistic sharing for offloading mobile traffic. We propose a tag-assisted social-aware D2D sharing framework, TASA, with corresponding optimization models, architecture design, and communication protocols. Through extensive simulations based on real data traces, we demonstrate that TASA can offload up to 78.9 percent of mobile traffic effectively.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| 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