计算机应用与软件2025，Vol.42Issue(4)：303-310,339,9.DOI:10.3969/j.issn.1000-386x.2025.04.043
基于深度强化学习的微服务链动态负载均衡算法
DYNAMIC LOAD BALANCING ALGORITHM OF MICROSERVICE CHAIN BASED ON DEEP REINFORCEMENT LEARNING
摘要
Abstract
More and more cloud services are shifting from monolithic architecture to microservice architecture.Under the microservice architecture,requests will traverse multiple microservices to form a microservice chain.Multiple microservice chains may compete for resources,and the block of a single microservice may be transmitted to any related microservice chain and result in timeout,thus violating the service level objectives(SLO)requested by the user.This paper proposes a dynamic load balancing algorithm for microservice chains that integrates service mesh and deep reinforcement learning,which can satisfy user expectations as much as possible in the face of dynamically changing loads.Experimental results show that the performance of service-mesh based microservice chain split module is improved by more than 10 times compared with the existing methods,and the load balancing algorithm can reduce SLO violations by at least 46％comparedwith the benchmark method.关键词
微服务/微服务链/负载均衡/深度强化学习/服务网格Key words
Microservice/Microservice chain/Load balancing/Deep reinforcement learning/Service mesh分类
计算机与自动化引用本文复制引用
章苏尧..基于深度强化学习的微服务链动态负载均衡算法[J].计算机应用与软件,2025,42(4):303-310,339,9.基金项目
国家重点研发计划项目(2018YFB1703500). （2018YFB1703500）
