A survey on the network models applied in the industrial network optimization  

作　　者：Chao DONG Xiaoxiong XIONG Qiulin XUE Zhengzhen ZHANG Kai NIU Ping ZHANG 

机构地区：[1]Key Laboratory of Universal Wireless Communications,Ministry of Education,Beijing University of Posts and Telecommunications,Beijing 100876,China [2]Smart City College,Beijing Union University,Beijing 100024,China

出　　处：《Science China(Information Sciences)》2024年第2期81-99,共19页中国科学（信息科学）（英文版）

基　　金：This work was supported by Key Program of National Natural Science Foundation of China(Grant No.92067202);National Natural Science Foundation of China(Grant No.62071058);Key Laboratory of Universal Wireless Communications(BUPT),Ministry of Education,China(Grant No.KFKT-2022104).

摘　　要：Network architecture design is critical for optimizing industrial networks.Network architectures can be classified into small-scale networks and large-scale networks based on scale.Graph theory is an efficient mathematical tool for network topology modeling.For small-scale networks,their structure often has regular topology.For large-scale ones,the current body of work mainly focuses on random characteristics of network nodes and edges.Recently,widely used models include random networks,small-world networks,and scale-free networks.In this study,starting from the scale of the network,network modeling methods based on graph theory as well as their industrial applications,are summarized and analyzed.Moreover,a novel network performance metric,called system entropy,is proposed.From the perspective of mathematical properties,an analysis of its non-negativity and concavity is performed.The advantage of system entropy is that it can cover the existing regular networks,random networks,small-world networks,and scale-free networks,and has strong generality.The simulation results reveal that this proposed metric can achieve the comparison of various industrial networks under different models.

关 键 词：industrial network small-scale network large-scale network graph theory system entropy 

分 类 号：O157.5[理学—数学]