基于DDD和K-Means的汽车服务系统微服务划分方法研究
Research on Microservice Segmentation Method for Automotive Service System Based on DDD and K-Means
李超 1蔡明高 2曹愚 1洪英杰1
作者信息
- 1. 江苏第二师范学院,南京 210013
- 2. 一汽(南京)科技开发有限公司,南京 210013
- 折叠
摘要
近年来,随着汽车领域数字化、网络化、智能化的加速发展,传统的软件架构方法面临着巨大挑战.微服务架构因其敏捷性、可伸缩性、灵活性等特性,成为软件工程中流行的一种架构.然而,将汽车服务系统从传统的架构拆分为多个微服务架构缺乏有效的划分标准.针对这一问题,本文提出了一种基于领域驱动设计(domain-driven design,DDD)和K-Means算法的汽车服务系统微服务划分方法.根据微服务的特点和汽车服务业务功能架构,确定业务逻辑与服务的映射关系,进而构建加权图,在此基础上通过K-Means算法得到最优的微服务划分方案.实验结果表明,使用该方法划分的微服务在可靠性、耦合性、容错性、自治性等方面具有一定的优势.
Abstract
With the rapid development of technology in the automotive field in recent years,the traditional approach to software architecture is facing challenges.Microservice architecture has become a popular architecture in software engineering because of its agility,scalability,flexibility,and other characteristics.However,there is a lack of effective partition criteria for splitting the automotive service system from the traditional architecture into multiple microservices.In order to solve this problem,this paper proposes a microservice partitioning method based on DDD(domain-driven design)and K-Means algorithm for automotive service system.According to the characteristics of microservices and the functional architecture of automotive service business,the mapping relationship between business logic and service is determined,and then a weighted graph is constructed,and the optimal microservice partition scheme is obtained through the K-Means algorithm.Experiments have shown that microservices partitioned using this method have certain advantages in reliability,coupling,fault tolerance,autonomy,and other aspects.
关键词
微服务/DDD/K-Means算法Key words
Microservices/DDD/K-Means Algorithm引用本文复制引用
出版年
2024
NETL
NSTL
万方数据