IEEE 802.15.4 Beaconing Strategy and the Coexistence Problem in ISM Band
Bibliographic record
Abstract
Over a home area network, between smart appliances and the smart meter, and over an 802.15.4g smart utility network, from a smart meter toward the utility center, IEEE 802.15.4 assists with advanced metering infrastructure components in a smart grid. Adopting the synchronous beacon-enabled mode of the IEEE 802.15.4 standard provides a slotted framework for low-power, real-time collection, and distribution of power information. However, the shared nature of the industrial, scientific, and medical (ISM) band introduces the beacon corruption issue, and confronts the 802.15.4-based network with service interruptions and large delays. This paper, experimentally and analytically, studies how interference from collocated networks affects the beaconing functionally and, consequently, network performance. Investigations indicate that beaconing contributes in low-power and low-delay communications over an 802.15.4 network only when its proper operation is guaranteed over a coexistent environment like ISM band; otherwise, the application delay is significantly compromised. In this regard, a standard-conforming enhancement, called the beacon corruption recovery scheme (BCRS), is proposed to mitigate effects of coexistence on beaconing performance by migration of the network to a cleaner channel. Simulation results show that by applying the BCRS, an 802.15.4 network experiences a less fragmented accesses to the medium and better fulfills real-time bidirectional flow of monitoring information.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".