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A Service Performance Aware Scheduling Approach in Containerized Cloud

机译:容器化云中的服务性能感知调度方法

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Due to the dynamic and uncertainty of users' demand for services, the resources that services depend on and the relationship between services, ensuring service performance has become a basic requirement of container cloud. There are many factors that affect service performance. Besides taking basic resources for carrying services into consideration, we also considered the delay between services caused by the relationship between services as a factor to ensure service performance, designed a container cloud dynamic monitoring framework for service performance, and proposed a service scheduling method at runtime. The design of framework can monitor service performance from two aspect of basic resources and service performance. The proposed method transforms the performance-based service scheduling problem into a planning problem that is constrained by the usage of basic resources and the delay between services. Furthermore, the proposed method generates the optimal service scheduling scheme effectively through particle swarm optimization algorithm. Compared with K8s scheduling method, the feasibility and effectiveness of this method were verified. Experimental results showed that this method could reduce the delay between services while ensuring the resource utilization and balance of the container cloud environment, so that effectively guarantee the service performance.
机译:由于用户对服务需求的动态性和不确定性,服务所依赖的资源以及服务之间的关系,确保服务性能已成为容器云的基本要求。有许多因素会影响服务性能。除了考虑承载服务的基本资源外,我们还考虑了由于服务之间的关系而导致的服务之间的延迟,这是确保服务性能的一个因素,设计了一个用于服务性能的容器云动态监控框架,并提出了一种运行时的服务调度方法。框架的设计可以从基本资源和服务性能两个方面监视服务性能。所提出的方法将基于性能的服务调度问题转换为一个计划问题,该问题受到基本资源的使用和服务之间的延迟的约束。此外,该方法通过粒子群优化算法有效地生成了最优服务调度方案。通过与K8s调度方法的比较,验证了该方法的可行性和有效性。实验结果表明,该方法可以在保证资源利用率和容器云环境平衡的同时,减少服务之间的延迟,从而有效地保证了服务性能。

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