MicroService Architecture (MSA) is gaining rapid popularity for developing large-scale IoT applications for deployment within distributed and resource-constrained Fog computing environments. As a cloud-native application architecture, the true power of microservices comes from their loosely coupled, independently deployable and scalable nature, enabling distributed placement and dynamic composition across federated Fog and Cloud clusters. Thus, it is necessary to develop novel microservice placement algorithms that utilise these microservice characteristics to improve the performance of the applications. However, existing Fog computing frameworks lack support for integrating such placement policies due to their shortcomings in multiple areas, including MSA application placement and deployment across multi-fog multi-cloud environments, dynamic microservice composition across multiple distributed clusters, scalability of the framework, support for deploying heterogeneous microservice applications, etc. To this end, we design and implement MicroFog, a Fog computing framework providing a scalable, easy-to-configure control engine that executes placement algorithms and deploys applications across federated Fog environments. Furthermore, MicroFog provides a sufficient abstraction over container orchestration and dynamic microservice composition. The framework is evaluated using multiple use cases. The results demonstrate that MicroFog is a scalable, extensible and easy-to-configure framework that can integrate and evaluate novel placement policies for deploying microservice-based applications within multi-fog multi-cloud environments. We integrate multiple microservice placement policies to demonstrate MicroFog's ability to support horizontally scaled placement, thus reducing the application service response time up to 54%.
翻译:微服务架构(MSA)在开发大规模IOT应用程序以在分布式和资源限制的雾计算环境中进行部署方面,正在迅速受到欢迎。作为一个云型应用架构,微服务的真正力量来自其松散、可独立部署和可扩展的性质,使分布式和动态构成能够跨越联盟化的雾和云群。因此,有必要开发新的微服务配置算法,利用这些微观服务特性来改进应用程序的性能。然而,现有的微服务计算框架缺乏对整合这种配置政策的支持,因为它们在多个领域存在缺陷,包括管理服务应用程序的配置和跨多功能多功能库环境的部署、多种分布式组合的动态微观服务构成、框架的可扩展性、支持采用多种微服务应用程序等。为此,我们设计和实施MicFog计算框架,提供可缩放式、易配置式控制引擎,用于实施定位算法和在联邦化的雾式反应环境中部署。此外,微软软化软件为集装箱配置和动态缩式缩化系统应用提供了足够抽象的缩缩缩缩缩缩缩应用政策。因此,对多功能配置框架进行了评估,对多种配置框架进行了多种应用进行了多功能评估,对多种应用进行了多种应用进行了评估。