Abstract:
Performance tuning improves system performance and reduces cloud computing resources needed to support an application. Cloud performance tuning must be automated due to the growing number of parameters and system complexity.
Modern tuning methods use either experience or data. Data-driven tuning’s broad applicability is drawing attention. Data-driven methods cannot simultaneously address sample scarcity and high dimensionality. ClassyTune is a data-driven cloud configuration tuning tool.
ClassyTune auto-tunes using machine learning classification. This exploitation induces more training samples without increasing input dimension. ClassyTune outperforms expert tuning and state-of-the-art auto-tuning solutions in high-dimensional configuration space. Performance tuning reduces computing resources needed to run an online stateless service by 33%.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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