Efficient Resource Configuration and Bandwidth Allocation for IIoT with Edge-Cloud Computing

With the emerging of mobile edge-cloud computing, the traditional cloud-based architecture for the Industrial Internet of Things (IIoT) can be improved effectively by integrating edge computing technology. However, due to the limited computation resources of edge servers and the unstable communication delay introduced by the cloud, it is difficult to guarantee the service quality of the IIoT applications. To address this issue, we first propose a collaborative edge-cloud architecture for IIoT, in which edge servers can migrate reliable computation resources from the cloud to guarantee service quality. Then, aiming at minimizing the migrating cost and communication delay, we formulate a long-term utility optimization problem, which integrates resource configuration and bandwidth allocation. Finally, we propose an efficient resource configuration and bandwidth allocation mechanism to obtain the optimal bandwidth and computation resources. Simulation shows that our proposed scheme has better performance on the profitability compared to other schemes.