RBS: A Reliable Broadcast Service for Large-Scale Low Duty-Cycled Wireless Sensor Networks
Bibliographic record
Abstract
Broadcast service is widely used during the life time of a wireless sensor network (WSN), such as networking setup, data collection/storage and query answering. In the past few years, many works have been done to improve its efficiency by reducing redundant broadcast messages. However, most of these works assume that all sensor nodes are active throughout a broadcast process and thus are difficult to be deployed in low duty-cycled WSNs, where sensor nodes switch between work and sleep to save energy and extend the network's life time. This problem is further aggravated by the difficulties to achieve global synchronization and rigid work-sleep schedules as the number of sensor nodes increases. To solve this problem, this paper remodels the broadcast problem to consider low duty-cycle and shows the lower bounds for time and message costs. We then propose an adaptive algorithm for dynamic message forwarding scheduling in this context, which enables a reliable and efficient broadcast service with low delay. Also, we demonstrate by extensive simulations that the proposed algorithm is not only robust against wireless communication loss but also performs close to optimal in terms of both time and message costs.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".