Availability and Sustainability Aware Service Function Chains (SFC) Allocation and Embedding in Edge-Cloud Continuum
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
The rapid evolution of network services, driven by innovations like virtualization and edge computing, has transformed the way modern applications are deployed and managed. Service Function Chains (SFC) formed by putting Virtual Network Functions (VNFs) in a particular order enable flexible and scalable network solutions. However, their virtualized nature introduces new challenges, including their availability and sustainability. Their joint balancing in SFCs deployment is crucial to meet the stringent requirements of next-generation networks. This study presents a novel approach for availability and sustainability-aware SFCs allocation and embedding in the edge-cloud continuum. It introduces embedding policies tailored to prioritize availability, reduce carbon footprint, or achieve a tradeoff between the two. Simulated Annealing (SA), Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) are employed to optimize VNF redundancy strategies. Simulation results demonstrate the effectiveness of the proposed methods, achieving robust fault tolerance while minimizing carbon footprint. The tradeoff-aware policy and PSO based redundancy strategy achieves 95.88% availability while cutting the carbon footprint by 37.6%.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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