Effects of Relaying on Network Lifetime in 2.4GHz IEEE802.15.4 Based Body Area Networks
Bibliographic record
Abstract
Relaying is a major technique to increase network lifetime in wireless sensor networks (WSNs) and body area networks (BANs). The results of relaying studies highly depend on power consumption model of relay's transmitter and receiver radio, channel and mobility models. In this work, we study the effect of relaying with 2.4GHz IEEE802.15.4 modules on network lifetime. We analytically derive the energy expenditure of relays in which we use the path loss probability distribution function (PDF) over links, which is derived from our link characterization using micaZ motes, and the existing power consumption models. It turns out that in order for relaying to be beneficial to network lifetime and for the same transmitter power amplifier efficiency, receive power consumption of IEEE802.15.4 widely used RF modules, e.g., micaZ motes are required to be decreased. For instance, receive power of 17mW helps us achieve 25% more lifetime with 3-relay scheme than single-hop transmission over ankle-waist link during walking, whereas with the current receiver, we achieve 12% less lifetime compared to single-hop scenario.
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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 | 0.003 |
| 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) | 0.001 | 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".