Joint Resource Allocation and Online Virtual Network Embedding for 5G Networks
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
Next generation (5G) wireless networks are expected to accommodate proliferation of connected devices and multimedia services. To support multimedia services in an agile, cost-effective, and flexible way, network virtualization is a potential solution. This paper investigates service- oriented network virtualization for 5G wireless networks, to efficiently allocate heterogeneous resources to accommodate multimedia services. Specifically, we study joint resource allocation for virtual network requests (VNRs) and online embedding the resultant VNRs in core networks (CNs). With the deployment of multiple traffic aggregation points (TAPs) in radio access networks (RANs), the end-to- end traffic from heterogeneous access technologies can be aggregated and then grouped based on their destinations. Queueing models are developed in determining the minimal capacity required at each core network element. Virtual network embedding (VNE) in the core network is further proposed to achieve efficient physical resource sharing in CNs. Simulation results validate the VNE process in core networks based on the optimized capacities.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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