云计算中基于数据流图的微服务划分方法  

Data Flow Graph Based on Microservice Partitioning Method in Cloud Computing

作　　者：钱峥远 王顺 曾国荪[1,2] 

机构地区：[1]同济大学计算机科学与技术系,上海 [2]国家高性能计算机工程技术中心同济分中心,上海

出　　处：《计算机科学与应用》2021年第12期3060-3069,共10页Computer Science and Application

摘　　要：容器化微服务架构是当前云计算开发的主要形式,将业务功能合理地划分为多个微服务是先决条件。因此,本文开展微服务自动划分方法研究。以数据流图作为划分基础,定义图中的分支、存储交互和普通计算三类节点,增加对数据流的频度级以及长度级的描述,重点关注数据流图中“始和终”两两外部实体间的正常处理流程。通过对数据流图中的处理流程进行遍历搜索,得到高业务内聚性的潜在微服务划分,进一步对处理流程进行分割与合并,减少微服务划分的功能模块冗余和服务间通信开销,最后得到高内聚、低耦合、少冗余的微服务划分结果。ERP应用实例分析,验证了本文划分方法的正确性,微服务运行结果相较于单体服务性能上有明显的提升。Containerized microservice architecture is the main form of cloud computing development at present. Dividing the business functions into multiple microservices reasonably is a prerequisite. Therefore, this paper carries out a research on automatic microservice partitioning method. In this paper, based on the division of the data flow diagram (DFD), the method defines the store interaction nodes, branch nodes and common computing nodes. It also increases the description of data flows in DFD, which contains frequency level and the length level. The method uses data flow diagram and focuses on the normal processing flows between source and target external entities. By searching normal processing flows, the method can get potential microservice decomposition with high business cohesion. Then the method splits and merges the potential microservice decomposi-tion to reduce functional module redundancy of microservices and communication overhead between microservices. Finally, the method gets the results of microservice partitioning with high cohesion, low coupling and little redundancy. Through the application verification on partitioning of basic ERP system, the correctness of the partitioning method in this paper and the high performance of microservice partitioning results are proved.

关 键 词：云计算 容器化微服务 数据流图 微服务划分 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]