A user‐centric cooperative edge caching scheme for minimizing delay in 5G content delivery networks
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Bibliographic record
Abstract
Abstract This paper investigates the problem of user‐centric cooperative edge caching in content delivery networks to leverage service provisioning at the network edge and to improve the quality of experience by minimizing the end‐to‐end delay. By taking advantage of the major characteristics in fifth‐generation networks, users can access contents not only from the nearest small base station (SBS) but also from other SBSs in the vicinity that have the requested precached contents. In the proposed scheme, a user‐centric delivery approach is considered in such a way that the base station can respond to the user request as long as it has enough resources. To this end, a caching algorithm is introduced whereby a group of SBSs cooperatively share storage and decide on the caching policy together aiming to cache as much contents as possible under the capacity constraint. Moreover, a modified matching theory is used for content delivery taking the bandwidth requirements into account. Simulation results show that the proposed scheme can achieve 99.5% local serve ratio when the SBS has a caching capacity of 40 % the overall file size, and 20 available communication channels for content distribution.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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