Performance of mobile wireless sensor network communication with 6LoWPAN
Bibliographic record
Abstract
This paper explores IPv6 in mobile wireless sensor networks (WSNs). An indoor WSN mobile sensor network testbed of length 24m was built and used for mobile WSN testing. The test network enabled the use of one or two moving nodes and six stationary nodes. A Java based web application called WSNWeb was implemented that displays and records real-time route topology changes and received sensor data. We created 65 test cases with one or two moving nodes, with variable velocities, routing table update periods (RTUPs) and data packet transmission rates. The effect of these parameters on quality of service was measured in terms of packet loss and on time packet loss (OTPL), a novel quality of service metric introduced in this paper. Results indicate that 6LoWPAN can accommodate communication with acceptable packet loss among nodes moving at a walking pace with data transmission frequencies up to 10 Hz and a RTUP as fast as 0.6 s. The highest observed packet loss and OTPL was 2.97% and 0.87%, respectively.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".