Incentive Engineering at Congested Wireless Access Points Using an Integrated Multiple Time Scale Control Mechanism
Bibliographic record
Abstract
Wireless networks are playing an increasingly important role for voice and data communications. It is estimated that the number of wireless network subscribers soon exceeds the number of wireline network subscribers. To efficiently support a large number of mobile users with a diversity of applications utilizing the scarce and limited radio resources in wireless networks, many resource allocation mechanisms have been proposed based on different metrics. Nevertheless, the fundamental problem of how to apply business rules to optimize configuration of devices, services and networks has not been widely addressed in most proposed resource management solutions. In this paper, we propose a novel incentive engineering mechanism called the integrated multiple time scale control (IMTSC) mechanism that integrates users' objectives of service differentiation and utility maximization with service providers' objectives of maximizing revenue and network efficiency. IMTSC utilizes a multiple time scale control mechanism with cumulus points to track each user's instantaneous traffic for better control of temporary network congestion, and the nuglet mechanism for admission control accounting for multiple charging factors. We provide a qualitative evaluation to show that our IMTSC mechanism provides a good balance among various perspectives that define the overall performance of a charging scheme
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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 | 0.001 |
| 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 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".