DSC: Cooperation Incentive Mechanism for Multi-Hop Cellular Networks
Bibliographic record
Abstract
Muli-hop cellular network is a promising network architecture which incorporates the ad hoc characteristic into the cellular system aiming to improve current cellular network performance. Unlike single hop cellular network, due to involving autonomous devices in packet forwarding, routing process suffers from new security challenges which endanger the practical implementation of the network. One security challenge is that selfish devices do not relay other nodes' packets because cooperation consumes their resources and does not provide any immediate advantages. Selfish nodes degrade the network throughput, connectivity and power consumption. In order to stimulate the nodes' cooperation, we propose a micro-payment mechanism to reward the forwarding nodes and charge the communicating ones. The security analysis shows that the proposed mechanism is robust against rational attacks, and it can thwart some irrational ones. To evaluate the cost of applying our mechanism, an implementation model is proposed. The performance analysis based on the implementation model demonstrates that the overhead is acceptable.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 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".