Detection and prevention of selfish and misbehaving nodes at MAC layer in mobile ad hoc 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
In wireless networks all nodes contending to access the medium are supposed to follow the rules of the Medium Access Control (MAC) layer. Wireless Medium Access Control (MAC) protocols such as IEEE 802.11 use a distributed contention resolution mechanism for sharing the wireless channel. The hosts competing for access to the channel are required to wait for a “back off” interval, randomly selected from a specified range, before initiating a transmission. Selfish nodes (or misbehaving nodes) tempt to manipulate their back off parameters to gain more access to the channel, and hence have higher performance than their fair share. Here, the problem of detection of node misbehavior in the MAC layer, with the objective to provide an optimum performance is being considered. This framework captures the presence of uncertainty of attacks.
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 | 0.000 | 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