广东工业大学学报2025，Vol.42Issue(5)：96-104,120,10.DOI:10.12052/gdutxb.240068
基于模糊图神经网络的工业互联网服务组件编排方法
Fuzzy Graph Neural Network-based Industrial Internet Service Component Orchestration Method
摘要
Abstract
In industrial internet environments,industrial software systems are usually large-scale and with a complex and heterogeneous array of software systems and physical devices.Based on the unified service-oriented and component-based encapsulation of heterogeneous devices and software objects,diverse applications of industrial software systems can be flexibly constructed through the orchestration of service components.However,it usually requires high efficiency of service orchestration and the assurance of service quality.To enhance the efficiency of service component orchestration and ensure service quality in industrial internet environments,this paper proposes a service component orchestration method called FGraphSAGE_GA,which formalizes the convert the component orchestration problem in industrial internet environments into a link prediction problem within a graph structure.It employs a supervised learning approach to train the prediction model.For the new service component orchestration problem,the trained model performs probabilistic predictions to narrow down the candidate space,followed by the optimization of the service component orchestration plan using a genetic algorithm.Experiments were conducted on two different datasets for service component orchestration problems of three different scales,and experimental results show that the proposed FGraphSAGE_GA algorithm has good performance in terms of service quality and orchestration efficiency.关键词
工业互联网/服务组件编排/图神经网络/模糊系统/遗传算法Key words
industrial internet/service component orchestration/graph neural network/fuzzy system/genetic algorithm分类
信息技术与安全科学引用本文复制引用
刘岸鑫,程良伦,王涛..基于模糊图神经网络的工业互联网服务组件编排方法[J].广东工业大学学报,2025,42(5):96-104,120,10.基金项目
国家自然科学基金联合基金资助集成项目(U20A6003) （U20A6003）
