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Programming framework and infrastructure for self-adaptation and optimized evolution method for microservice systems in cloud-edge environments

机译:用于云边缘环境中的微服务系统的自适应和优化演化方法的编程框架和基础设施

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Edge computing technologies facilitate the deployment of services on nearby edge servers with a large number of end users and their mobile devices to fulfill personalized demands. Owing to frequent changes in user mobility and demands, service systems deployed in an edge-cloud environment must continuously adapt to ensure that the quality of service (QoS) perceived by the end users is maintained at a stable and satisfactory level. As it is difficult for system operation engineers to manually deal with such frequent and large-scale evolution due to problems of cost and efficiency, self-adaptation of the system is essential. In this paper, we present a programming framework for microservices (EPF4M) and an infrastructure for self-adaptive microservice systems (EI4MS) for the cloud-edge environment based on microservice architecture. Our study follows a "monitoring-analyzing-planning-execution" control loop that empowers the service systems to redeploy the services according to changes in the QoS. A two-phase strategy is adopted to minimize the side effects of the loop on the performance of the service system. A prototype of this framework and infrastructure has been open-sourced and verified through experiments conducted in a real cloud-edge environment. The results demonstrate the usefulness and advantages of our approach.
机译:Edge Computing Technologies有助于在附近的边缘服务器上部署服务,其中包含大量最终用户及其移动设备以满足个性化需求。由于用户移动性和需求的频繁变化,在边缘云环境中部署的服务系统必须不断适应,以确保最终用户感知的服务质量(QoS)保持稳定且令人满意的水平。由于系统运营工程师难以通过成本和效率的问题手动处理如此频繁和大规模的演变,因此系统的自适应是必不可少的。在本文中,我们为基于微服务架构的云边缘环境的自适应微服务系统(EI4MS)提供了一种用于微服务(EPF4M)的编程框架和基础设施。我们的研究遵循“监控分析规划 - 执行”控制循环,使服务系统能够根据QoS的更改重新部署服务。采用两相策略来最小化环路对服务系统性能的副作用。该框架和基础设施的原型已经开放并通过真实云边缘环境中进行的实验进行验证。结果表明了我们方法的有用性和优势。

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