Information Dissemination With Service-Oriented Incentive Mechanism in Industrial Internet of Things
Bibliographic record
Abstract
As one of the essential paradigms of Industrial 4.0, the Industrial Internet of Things (IIoT) challenges existing data management and information services by supporting computational-intensive applications, in which devices share and receive information through interactions under resource constraints. When there exist diverse service requirements of IIoT applications, information dissemination will be more likely driven by service-oriented incentives. In this article, a novel information dissemination process with the service-oriented incentive mechanism is analyzed and modeled in IIoT, which depicts the dynamical evolution of IIoT devices’ interactions. In particular, the characteristics of service-oriented activating and dissemination degenerating are considered due to the unique capability of IIoT devices. Extensive theoretical and simulation results verify the dynamical behaviors of information dissemination, including the propagation threshold, equilibrium, and stability. In addition, comparative simulations have demonstrated the service-oriented incentive mechanism further expands information diffusion by driving the participation of IIoT devices.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".