Genetic-based algorithms for resource management in virtualized IVR applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Interactive Voice Response (IVR) is a technology that allows automatic human-computer interactions, via a telephone keypad or voice commands. The systems are widely used in many industries, including telecommunications and banking. Virtualization is a potential technology that can enable the easy development of IVR applications and their deployment on the cloud. IVR virtualization will enable efficient resource usage by allowing IVR applications to share different IVR substrate components such as the key detector, the voice recorder and the dialog manager. Resource management is part and parcel of IVR virtualization and poses a challenge in virtualized environments where both processing and network constraints must be considered. Considering several objectives to optimize the resource usage makes it even more challenging. This paper proposes IVR virtualization task scheduling and computational resource sharing (among different IVR applications) strategies based on genetic algorithms, in which different objectives are optimized. The algorithms used by both strategies are simulated and the performance measured and analyzed.
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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 | 0.001 | 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 | 0.000 |
| 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 it