Application of the DEVS and Cell-DEVS formalisms for modeling networking applications
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
We present the use of DEVS and Cell-DEVS formalisms to model different approaches in networking applications. We discuss various applications of discrete event system specifications for modeling and simulation of Wireless networks and Wireless Sensor Networks (WSN). We discuss how to use the Cell-DEVS formalism to model a WSN for investigating on stochastic properties of malware propagation and the intrinsic characteristic of WSN. We also discuss the use of DEVS to model a cellular network including a wide geographical area, various Cells and varied User Equipment. Finally, we discuss how to use the cell DEVS formalism to model mobile networks, and how the Cell-DEVS formalism can be used to track mobile user movement in a covered area. The latter model tries to find out the number of Base Stations which cover a mobile user in different location of an area and how to improve QoS based on different configurations (in particular for the UEs near the cell borders).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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