Scheduling and routing methods for cognitive radio sensor networks in regular topology
Bibliographic record
Abstract
Abstract Wireless sensor network of regular topology is efficient in area covering and targets locating. However, communications with fixed channels lead to low spectrum efficiency and high probability of conflicts. This paper proposes economical timeslots‐and‐channels allocation methods for scheduling links in square, triangle, and hexagon lattice topologies. Based on these scheduling methods in square lattice, the authors explore routing methods for load balance and delay minimization, respectively, and compare their effects on transmission delay and energy consumption. The OMNet++‐based simulation for square lattice verified the effectiveness of scheduling methods for improving network throughput and made performance comparison among different scheduling methods. It also proved that delay minimization‐oriented routing helps to reduce the energy consumption for node standing by and load balance‐oriented routing helps to reduce the energy consumption for packets transmission. However, there is trade‐off between the reductions of the two types of energy consumptions. The authors further propose the idea of hybrid routing with the two aforementioned routing methods for reducing overall energy consumption and explore the challenges and countermeasures for hybrid routing optimization. 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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".