Maximizing the Lifetime of Wireless Sensor Networks through Optimal Single-Session Flow Routing
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Bibliographic record
Abstract
Wireless sensor networks are becoming increasingly important in recent years due to their ability to detect and convey real-time, in-situ information for many civilian and military applications. A fundamental challenge for such networks lies in energy constraint, which poses a performance limit on the achievable network lifetime. We consider a two-tier wireless sensor network and address the network lifetime problem for upper-tier aggregation and forwarding nodes (AFNs). Existing flow routing solutions proposed for maximizing network lifetime require AFNs to split flows to different paths during transmission, which we call multisession flow routing solutions. If an AFN is equipped with a single transmitter/receiver pair, a multisession flow routing solution requires a packet-level power control at the AFN so as to conserve energy, which calls for considerable overhead in synchronization among the AFNs. In this paper, we show that it is possible to achieve the same optimal network lifetime by power control on a much larger timescale with the so-called single-session flow routing solutions, under which the packet-level power control and, thus, strict requirement on synchronization are not necessary. We also show how to perform optimal single-session flow routing when the bit-rate of composite flows generated by AFNs is time-varying, as long as the average bit-rate can be estimated
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it