Energy Efficiency on Fully Cloudified Mobile Networks: Survey, Challenges, and Open Issues
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fully cloudified mobile network infrastructure, which is featured by the joint deployment of heterogeneous cloud radio access networks and edge computing, will successfully cope with the data deluge by densely deploying virtualized wireless base stations and servers while providing the system design with high flexibility, reliability, availability, and scalability. On the other hand, the massive replication of the wireless and computing infrastructure will significantly increase the energy footprint to prohibitive levels. In order to gain actionable insights on energy-efficiency for a fully cloudified mobile network infrastructure, this paper first presents a comprehensive survey of the recent research breakthroughs on each building block of the system, namely: remote radio heads, baseband unit pool, fronthaul, backhaul, HetNet, and edge and cloud computing. Next, we consolidate the discussion with the challenges and open issues of a joint operation.
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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 | 0.005 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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