Credit based task scheduling process management in fog computing

Fog computing platform, characterized by pushing the cloud services to the network edge, is a promising solution to support and strengthen the traditional embedded system. In recent years, with the advent of the Internet of Things (IoT) and Block chain technology, fog computing is introduced as a powerful complement to the cloud to handle the IoT's data. Fog computing helps to reduce transmission latency and monetary cost for cloud resources. However, fog resources are minimal comparing to the cloud. In this research, we aim to design a scheduling architecture based on the collaboration between cloud and fog computing. Also, we attempt to solve the following issue: minimizing the makespan of large scale compute-intensive applications in a highly distributed platform of cloud-fog computing. We first formulate the task scheduling problem, then we propose a task scheduling algorithm to achieve the balance to task assignment between fog and cloud along with reducing the makespan of task execution. Our evaluation shows that the system algorithm achieves around 40.1% in makespan reduction than existing algorithms.