Emulation of Large-Scale LTE Networks in NS-3 and CORE: A Distributed Approach
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
Long Term Evolution (LTE) is a promising technology to be used for Mission-Critical Networks (MCNs); emulating such technology is important to test different scenarios before real deployment. However, using the Network Simulator (NS-3) to simulate large-scale LTE networks has proven to be very time consuming. Hence, there is a need to speed up such simulations in order to facilitate real-time emulation and interaction of large-scale LTE networks with external systems. In this paper, we propose a new approach to enable the emulation of large-scale LTE networks by employing distributed topologies along with the Message Passing Interface (MPI) protocol. The proposed approach is integrated with the Common Open Research Emulator (CORE) to enable exchange of real-time traffic between the simulated LTE network and Hardware-In-the Loop (HIL). Performance studies were carried out to evaluate the scaling performance of emulated LTE networks in real time. The results show that distributed implementation succeeds in running scenarios within the wall-clock time.
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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 | 0.001 | 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 it