An energy‐efficient utility‐based distributed data routing scheme for heterogenous sensor networks
Bibliographic record
Abstract
Abstract A utility‐based distributed data routing algorithm is proposed and evaluated for heterogeneous wireless sensor networks. It is energy efficient and is based on a game‐theoretic heuristic load‐balancing approach. It runs on a hierarchical graph arranged as a tree with parents and children. Sensor nodes are considered heterogeneous in terms of their generated traffic, residual energy and data transmission rate and the bandwidth they provide to their children for communication. The proposed method generates a data routing tree in which child nodes are joined to parent nodes in an energy‐efficient way. The principles of the Stackelberg game, in which parents as leaders and children as followers, are used to support the distributive nature of sensor networks. In this context, parents behave cooperatively and help other parents to adjust their loads, while children act selfishly. Simulation results indicate the proposed method can produce on average more load‐balanced trees, resulting in over 30 % longer network lifetime compared with the cumulative algorithm proposed in the literature. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.005 | 0.003 |
| 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".