The Fog computing paradigm utilises distributed, heterogeneous and resource-constrained devices at the edge of the network for efficient deployment of latency-critical and bandwidth-hungry IoT application services. Moreover, MicroService Architecture (MSA) is increasingly adopted to keep up with the rapid development and deployment needs of fast-evolving IoT applications. Due to the fine-grained modularity of the microservices and their independently deployable and scalable nature, MSA exhibits great potential in harnessing Fog and Cloud resources, thus giving rise to novel paradigms like Osmotic computing. The loosely coupled nature of the microservices, aided by the container orchestrators and service mesh technologies, enables the dynamic composition of distributed and scalable microservices to achieve diverse performance requirements of the IoT applications using distributed Fog resources. To this end, efficient placement of microservice plays a vital role, and scalable placement algorithms are required to utilise the said characteristics of the MSA while overcoming novel challenges introduced by the architecture. Thus, we present a comprehensive taxonomy of recent literature on microservices-based IoT applications placement within Fog computing environments. Furthermore, we organise multiple taxonomies to capture the main aspects of the placement problem, analyse and classify related works, identify research gaps within each category, and discuss future research directions.
翻译:雾计算模式在网络边缘利用分布式、多样性和资源紧缺的装置,以高效部署延缓关键和带宽饥饿的IOT应用服务;此外,越来越多地采用微服务架构,以跟上快速发展的IOT应用的快速开发和部署需求;由于微服务模块性精细以及其可独立部署和可扩缩的性质,管理事务协议在利用雾和云资源方面具有巨大潜力,从而产生像Osmology计算这样的新模式;集装箱管弦器和服务网格技术所帮助的微服务性质松散,使分布式和可扩缩的微观服务能够动态组成,利用分布式的Fog资源满足IOT应用的各种性要求;为此,高效安排微服务具有关键作用,需要可扩缩的安置算法,在利用上述管理事务协议的特性的同时克服结构带来的新挑战;因此,我们介绍了最近关于基于微观服务、带带带和服务网的网技术,使分布式和可扩缩缩缩缩缩微服务能够利用的微观研究的微观学系,并分析我们组织化的多种研究领域的主要研究领域,并分析与IOM相关研究的每个工作内部的分类。