Saturation throughput using different backoff algorithms in IEEE 802.15.4
Bibliographic record
Abstract
The IEEE 802.15.4 standard for the Low Rate Wireless Personal Area Networks (LR-WPANs)is popular and widely used for many areas of applications. The standard uses slotted CSMA/CA protocol in it's contention access period (CAP) in the beacon enabled mode. The protocol adopted a Binary Exponential Backoff (BEB)algorithm. In this paper, we investigate the saturation throughput of this standard using the existing BEB algorithm and compare it with three other backoff schemes - Exponential Increase Exponential Decrease (EIED), Exponential Increase Linear Decrease (EILD) and Exponential Increase Multiplicative Decrease (EIMD) algorithms. From the simulation results, it is found that EIED, EILD and EIMD perform better than the BEB for the higher loads. The EIED produces the highest throughput among all of these schemes.
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 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 | 0.001 |
| 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".