Runtime Resource Management with Multiple-Step-Ahead Workload Prediction

Modern embedded platforms need sophisticated resource managers in order to utilize their heterogeneous computational resources efficiently. Furthermore, such are subject fluctuating workloads that unforeseeable at design time. Predicting the incoming workload could enhance efficiency of management this situation. But is case? And, if so, how substantial improvement? Does multiple-step-ahead prediction contribute How precise must be improve decisions rather than cause harm? By proposing a prediction-based manager aims meeting task deadlines while minimizing energy usage, and by conducting extensive tests, we attempt provide answers aforementioned questions.