A SDN-Assisted Energy Saving Scheme for Cooperative Edge Computing Networks
Bibliographic record
Abstract
In this paper, an edge device sleeping mechanism is proposed to save energy in cooperative edge computing networks. Energy saving in the proposed scheme is obtained by implementing a software- defined networking (SDN)-assisted interactive On/Off operation on edge devices taking into account the quality of service (QoS) experienced by end-users. First, an optimization problem is formulated to reduce the number of active edge devices under the queueing probability constraint. Herein, edge devices are modeled as M/M/k queueing systems, whereas the square-root staffing rule is used to maintain the queueing probability below desired levels. Then, a load balancing mechanism is carried out to reduce the variations in resource utilization among edge devices. To this end, a discrete-time Markov chain (DTMC)-based algorithm is implemented to achieve the intended load balancing. Results show the effectiveness of the proposed scheme in achieving energy saving and maintaining the queueing delay at controlled levels.
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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 | 0.001 | 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 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".