Realistic physical layer modelling for georouting protocols in wireless ad-hoc and sensor networks
Bibliographic record
Abstract
Existing routing and broadcasting protocols for ad-hoc networks assume an ideal physical layer. In reality, an accurate representation of physical layer is required for analysis and simulation of multi hop networking in sensor and ad-hoc networks. This paper describes the model for the lognormal correlated shadow fading loss from the first principles of probability theory, and investigates the importance of correlation length while designing protocols for ad-hoc and sensor networks. Nodes that are geographically proximate often experience similar environmental shadowing effects and can have correlated fading. We consider the overall path loss (shadow fading & median path loss) based on antennas working at 2.4 GHz with heights ranging from 0.5 metres to 1.8 metres. Finally, we analyze and compare the performance of localized position based greedy algorithm used for Unit Disk Graph (UDG) and probabilistic progress based algorithm on the proposed shadowing model for different values of standard deviation (¿) of shadow fading to show the importance of both the shadow fading and correlation length.
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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 | 0.000 |
| 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 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".