An Intelligent Edge-Computing-Based Method to Counter Coupling Problems in Cyber-Physical Systems

Abstract

Cyber-physical systems (CPSs) have become more complex, more sophisticated, and more intelligent. In addition to this complexity, they have also been exposed to some important disturbances due to unintentional and intentional events since the number of cyber attacks has increased, and their behaviors have become more sophisticated. The openness, virtualization, and ubiquitous access traits of the combination of CPS and cloud computing may cause coupling problems. When malicious users or attackers simultaneously request the same physical nodes, it may lead to a failure of services as well as a security threat to the system. In this article, we design a low-coupling system based on the edge computing platform to counter coupling problems. The edge computing platform acts as a middleware platform and provides the scheduling method. Based on the edge computing platform and artificial intelligence technology, we design two buffer queues to reduce the coupling degree of the system in parallel. Moreover, we improve the Kuhn-Munkres algorithm to obtain the maximum matching between users' requests and resources to achieve optimal resource distribution. The experimental results indicate that the proposed edge-based scheme can effectively counter the coupling problem for CPSs.