Joint Resource Management in Cognitive Radio and Edge Computing Based Industrial Wireless Networks

The Fourth Industrial Revolution we are experiencing currently is reshaping the world by facilitating factories with intelligence and significantly improved manufacturing efficiency and flexibility. Among the key technologies to achieve Industrie 4.0, industrial wireless networking enables convenient and reliable connections among the machines, network devices, cloud servers and humans for both delay-sensitive traffic and delay-tolerant data delivery. In this paper, the Cognitive radio and Edge computing based Industrial wireless Network (CEIN) is introduced. In CEIN, edge computing handles the processing requirements of the data during its transmission, and is deployed close to the machines for immediate response to delay-sensitive industrial data that requires real-time processing. Cognitive radio technologies are also adopted to ensure efficient spectrum resource utilization for big delay- tolerant data transmission that contributes mostly to the industrial data traffic. Besides, we propose an optimal networking and computing resource management scheme for CEIN. The harvested spectrum bands are allocated to the network devices taking into account of the computing requirements of industrial data. Stochastic optimization is adopted to find the optimal allocation actions with low on-line computational complexity. Extensive simulation results are also presented to demonstrate the significant system performance improvement.