Real-Time Workload Allocation Optimizer for Computing Systems by Using Deep Learning

With the increase of the Internet of Things (IoT) business, the number of edge computing systems are rapidly increasing. Reducing the power consumption of these computing systems has become a social issue. For that purpose, we proposed and demonstrated the power consumption reduction method by the optimal task assignment technology. Specifically, for sequential real-time jobs, we proposed a workload allocation optimizer (WAO) to minimize the power consumption of computing systems. This assignment algorithm achieved a 13% power reduction compared to the worst job assignment.