Segment Routing Green Spine Switch Management Systems for Data Center Networks
Bibliographic record
Abstract
The datacenter is the core of most IT industries today. As a result, due to the exponential increase of information and services demanded from datacenters, it is projected that 14.1 zeta bytes of bandwidth would be needed to meet the current demands of data by the end of 2020 in USA datacenters alone. This would require a tremendous amount of energy to run those datacenters. Hence, in recent years there is more focus on reducing the energy consumption in a datacenter. This paper approaches this problem by utilizing Segment Routing based Green Spine Switch Management System (SR-GSSMS) to have an efficient bandwidth usage. The proposed approach makes it possible to deactivate some low utilized spine switches and links on the datacenter networks, which results in energy savings. The system also maintains the network performance when congestion or a link failure occurs. Our experimental results yielded up to a 78% energy savings on the spine-links, while maintaining the same traffic requirements.
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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 | 0.001 | 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 | 0.003 | 0.004 |
| 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".