Performance Characterization of Signaling Traffic in IMS Virtualized Network
Bibliographic record
Abstract
Virtualization gives different types of Mobile Virtual Network Operators (MVNO) the possibility to deploy their components more rapidly and at a lower cost. In this paper, we propose five scenarios for the virtualization of the IP Multimedia Subsystem (IMS) components and compare them to the non virtualized one. To assess the service quality of the signaling system in our proposed virtualized scenarios, we consider three signaling procedures, namely registration, voice session, and data session. This study investigates the delay for each signaling procedure as a performance metric. By applying a Markovian generic model to our scenarios, we calculate the pre-established performance metrics. Based on the comparison of the delays of each virtualized scenario with those of the non-virtualized one, we then evaluate the utility function, by which we mean the improvement or degradation of virtualized delays. Finally, we deduce the best scenario that ensures a good service quality for each MVNO type. The main results show that the virtualized Proxy Call Session Control Function (P-CSCF) represents the most efficient scenario for the MVNO voice type, while the scenario in which all CSCF components are virtualized provides the best results for the data type.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".