Modeling User Churning Behavior in Wireless Networks Using Evolutionary Game Theory
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Bibliographic record
Abstract
Churning of mobile users from one service provider to another is expected to become a common feature when the mobile users have freedom to choose the best wireless service. This churning behavior impacts both the technical and the economical aspects of wireless network design. In this paper, we model the churning behavior of wireless service users by using the theory of evolutionary game. We consider a system model consisting of WLAN hotspots where a wireless user can choose among different WLAN access points based on the performances and/or price. A continuous-time Markov chain model is established to capture the connection arrival and departure processes, as well as the rational and irrational churning behaviors of wireless service users. The evolutionary equilibrium, which is used to compute the average number of users choosing each wireless service, is considered as the solution. Based on this evolutionary game framework, we investigate two different possible pricing schemes, namely, non-cooperative and cooperative pricing schemes, for the wireless service providers. These schemes maximize individual revenue and total revenue, respectively, of the service providers. Performance analysis results are presented for the proposed modeling framework.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it