A complexity assessment framework with structure entropy for a cloud-edge collaborative manufacturing system

Abstract

The Industrial Internet of Things (IIoT), along with 5G and beyond networks, is driving a new era of revolution in intelligent manufacturing. However, the integration of more heterogeneous entities and intricate communication protocols complicates the enhanced manufacturing system, posing challenges for quantitatively assessing its complexity. To tackle this issue, a complexity assessment framework for the IIoT-enabled collaborative manufacturing system is proposed by combining the complex network and information entropy theory. Firstly, industrial entities in the physical space are mapped into a two-tier complex network taking into account the weights of various access communications. Secondly, an importance-aware structure entropy is introduced to capture the complexity of industrial networks from the communication perspective in the system. The experiments conducted on various network topological structures validate the proposed method and provide guidance for system design.