ANANKE: a Q-Learning-Based Portfolio Scheduler for Complex Industrial Workflows

Complex workflows that process sensor data are useful for industrial infrastructure management and diagnosis. Although running such workflows in clouds promises reduces operational costs, there are still numerous scheduling challenges to overcome. Such complex workflows are dynamic, exhibit periodic patterns, and combine diverse task groupings...