Cluster-based routing protocol for mobile sensor networks
Bibliographic record
Abstract
Hierarchical routing and clustering mechanisms in Wireless Sensor Networks (WSN) help to reduce the energy consumption and the overhead created when all the sensor nodes in the network are sending information to the central data collection point or base station. Most of the routing and clustering protocols currently used or proposed for WSN assume that the nodes are stationary. However, in applications like habitat monitoring or search and rescue, that assumption makes those clustering mechanisms invalid, since the static nature of sensors is not real. In this thesis, we present a Cluster-based ROuting protocol for MObile Sensor networks (CROMOS). The protocol considers the following design aspects: mobility of sensors, zones and routes maintenance, information update and communication between sensor nodes. A simulation model has been designed and developed to evaluate the performance of the proposed protocol. Simulation results and comparisons with different scenarios show the effectiveness and strengths of the CROMOS protocol. CROMOS shows a low routing and mobility overhead, while achieving a good performance in WSN using small zone sizes and sensors with low speed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".