A Simulation Model of IEEE 802.15.4 GTS Mechanism and GTS Attacks in OMNeT++ / MiXiM + NETA
Bibliographic record
Abstract
The IEEE 802.15.4 standard defines the PHY and MAC layer specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs). With the proliferation of many time-critical applications with real-time delivery, low latency, and/or specific bandwidth requirements, Guaranteed Time Slots (GTS) are increasingly being used for reliable contention-free data transmission by nodes within beacon-enabled WPANs. To evaluate the performance of the 802.15.4 GTS management scheme, this paper introduces a new GTS simulation model for OMNeT++ / MiXiM. Our GTS model considers star-topology WPANs within the 2.4 GHz frequency band, and is in full conformance with the IEEE 802.15.4 – 2006 standard. To enable thorough investigation of the behaviors and impacts of different attacks against the 802.15.4 GTS mechanism, a new GTS attacks simulation model for OMNeT++ is also introduced in this paper. Our GTS attacks model is developed for OMNeT++ / NETA, and is integrated with our GTS model to provide a single inclusive OMNeT++ simulation model for both the GTS mechanism and all known-to-date attacks against it.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".