Energy-efficient resource allocation in software-defined mobile networks with mobile edge computing and caching
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we study the energy-efficient resource allocation in software-defined mobile networks with mobile edge computing and caching. With the introduction of caching and computing functions in mobile networks, content sources need to be selected according to the distribution of contents in caches, the capability of computational resources and the status of networks. Moreover, the network needs to provision bandwidth on each link for data flows from the source to the destination by allocating backhaul and radio resources. In this framework, we formulate a novel optimization problem to jointly consider bandwidth provisioning and content source selection. To solve this problem efficiently, firstly the content source selection problem is decoupled from the bandwidth provisioning problem by deploying dual-decomposition method. Additionally, based on alternating direction method of multipliers, we develop decentralized schemes to solve the decoupled problems across links and base stations coordinated by a central controller. Simulation results are presented to show the performance of 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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