Towards LTE physical layer virtualization on a COTS multicore platform with efficient scheduling
Bibliographic record
Abstract
This paper explores the runtime behavior of a class of multiprocessor systems in specific contexts associated with cloud radio access network implementation. It specifically deals with task scheduling, run time behavior, and their characterization. It also relates to Network Functions Virtualization (NFVs) and especially with the constraints associated with virtualization of a Long Term Evolution (LTE) stack. To validate the effectiveness of different scheduling algorithms, an emulation of an LTE uplink virtualized stack is made. Experiments are carried out using a runtime system, StarPU, coupled with profiling tools, which allows characterizing the need for dedicated threads or cores to manage tasks within a server. Reported experimental results confirm the feasibility of software scheduling of an LTE uplink stack with two of the six tested algorithms. In addition, this paper explores distributing the scheduling load across multiple computing units, which is more efficient than implementations where the scheduler is centralized on a dedicated processor.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".