Network Slice Provisioning Taking Into Account Tenant Intents and Operator Policies
Bibliographic record
Abstract
Intent-based networking paradigm aims at easing the complexity of network management for operators/tenants. Intents are expressed as high-level requirements in terms of what is required and not how to achieve it with low level deployment and infrastructure details. A translation between what is required and how to achieve it is therefore needed. In the context of network automation, this translation and subsequent network management tasks must be performed automatically. Most of the work in this area has been focusing on the runtime phases. This paper is interested in the network slice design phase and proposes an approach for determining all the network slice solutions from tenant intents while taking into account operator policies. Therefore, these solutions will satisfy the tenant intents and comply automatically with the operator policies. Tenant intents consist of one or multiple required communication services and network slices along with their desired QoS characteristics. The operator’s policies specify the supported slice types with their QoS characteristics. This is the first step towards an automated approach for network slices design from tenant intents. The proposed approach is model based.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".