Joint VNF Placement and Multicast Traffic Routing in 5G Core Networks
Bibliographic record
Abstract
The software defined networking (SDN) enabled network function virtualization (NFV) architecture emerges as a cost-effective solution for service customization in fifth generation (5G) networks. In this paper, a joint traffic routing and virtual network function (VNF) placement problem is studied for a multicast service request accommodated over a physical substrate network, where the multipath traffic routing is considered between embedded VNFs. The joint problem is formulated as a mixed integer linear programming (MILP) problem to minimize the provisioning cost of both VNFs and links, under the physical network resource constraints, flow conservation constraints, and VNF placement rules. Since the problem is NP-hard, low complexity heuristic algorithms, with the consideration of both the single-path and multipath routing cases, are proposed to determine an efficient solution. Simulation results are presented to demonstrate the effectiveness and accuracy of the proposed heuristic algorithms especially for a large-size network.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".