Enhancing QoE-Aware Wireless Edge Caching With Software-Defined Wireless Networks
Why this work is in the frame
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Bibliographic record
Abstract
Software-defined networking and in-network caching are promising technologies in the next generation wireless networks. In this paper, we propose enhancing the quality of experience (QoE)-aware wireless edge caching with bandwidth provisioning in software-defined wireless networks (SDWNs). Specifically, we design a novel mechanism to jointly provide proactive caching, bandwidth provisioning, and adaptive video streaming. The caches are requested to retrieve data in advance dynamically according to the behaviors of users, the current traffic, and the resource status. Then, we formulate a novel optimization problem regarding the QoE-aware bandwidth provisioning in SDWNs with jointly considering in-network caching strategy. The caching problem is decoupled from the bandwidth provisioning problem by deploying the dual-decomposition method. Additionally, we relax the binary variables to real numbers so that those two problems are formulated as a linear problem and a convex problem, respectively, which can be solved efficiently. Simulation results are presented to show that the latency is decreased and the utilization of caches is improved in the proposed 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.006 | 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