Cocasting and power control for energy efficient information dissemination in WSNs
Bibliographic record
Abstract
This paper considers energy efficient information dissemination in Wireless Sensor Networks (WSNs) deploying co-operating nodes which by adjusting their transmission ranges minimize the total transmitted power in the network. Specifically, the design of routing protocols with a single relay node along a data path is proposed for multiple unicast sessions in a network with randomly distributed nodes. The protocols take advantage of topological diversity created by adapting the transmission power and exploit the benefits of network coding in a system where nodes are periodically generating data packets. Energy efficiency of the conventional, store-and-forward, and network coding based relaying schemes is analyzed in different propagation conditions and for various node densities. The best-case improvement in the energy efficiency achievable with network coding over store-and-forward is 25% for two node exchange of data. In WSNs, it is demonstrated through simulations that network coding offers realistically between 11% to 19% energy savings over the store-and-forward strategy. The deployment of the relaying node contributes to the improvement in energy efficiency over direct transmissions in a range of 80%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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".