{"title":"FogDEFTKube: Standards‐compliant dynamic deployment of fog service containers","authors":"Rajesh Thalla, S. Srirama","doi":"10.1002/spe.3354","DOIUrl":null,"url":null,"abstract":"The traditional cloud‐centric approach in IoT applications lack the speed and efficiency required for time‐critical tasks, resulting in network inefficiencies. To address this, the notions of Edge and Fog computing have emerged as alternatives. Fog computing facilitates the deployment of services and applications closer to the network's edge, lowering latency and allowing real‐time capabilities. It enhances reliability, fault tolerance, and connectivity in areas with spotty network coverage. Despite the fact that fog computing overcomes the limitations of cloud‐centric IoT processing, its adoption faces challenges like platform independence, interoperability, and portability. To tackle these challenges, the FogDEFT (Fog computing out of the box: Dynamic dEployment of Fog service containers with TOSCA) framework was developed. It complies to OASIS‐TOSCA standards and guarantees dynamic deployment of fog services on resource‐constrained devices while leveraging Docker containerization technology to ensure platform independence and interoperability. Due to its tight coupling with Docker Swarm, which is designed for medium‐sized deployments, the fogDEFT framework is constrained by Docker Swarm's limitations, hindering its ability to effectively manage large‐scale, automated, and resource‐efficient microservice deployments. To address these limitations, we propose FogDEFTKube, an extension of the FogDEFT architecture that incorporates Kubernetes for orchestration, Jenkins for continuous integration and deployment, and a comprehensive redefinition of the core capabilities of the FogDEFT architecture. This offers a promising solution that supports Kubernetes for handling scalable and highly available fog applications with ease while offering CI/CD. FogDEFTKube simplifies the modeling and deployment of fog services while abstracting the complexities of underlying fog networks.","PeriodicalId":21899,"journal":{"name":"Software: Practice and Experience","volume":"2 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software: Practice and Experience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/spe.3354","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The traditional cloud‐centric approach in IoT applications lack the speed and efficiency required for time‐critical tasks, resulting in network inefficiencies. To address this, the notions of Edge and Fog computing have emerged as alternatives. Fog computing facilitates the deployment of services and applications closer to the network's edge, lowering latency and allowing real‐time capabilities. It enhances reliability, fault tolerance, and connectivity in areas with spotty network coverage. Despite the fact that fog computing overcomes the limitations of cloud‐centric IoT processing, its adoption faces challenges like platform independence, interoperability, and portability. To tackle these challenges, the FogDEFT (Fog computing out of the box: Dynamic dEployment of Fog service containers with TOSCA) framework was developed. It complies to OASIS‐TOSCA standards and guarantees dynamic deployment of fog services on resource‐constrained devices while leveraging Docker containerization technology to ensure platform independence and interoperability. Due to its tight coupling with Docker Swarm, which is designed for medium‐sized deployments, the fogDEFT framework is constrained by Docker Swarm's limitations, hindering its ability to effectively manage large‐scale, automated, and resource‐efficient microservice deployments. To address these limitations, we propose FogDEFTKube, an extension of the FogDEFT architecture that incorporates Kubernetes for orchestration, Jenkins for continuous integration and deployment, and a comprehensive redefinition of the core capabilities of the FogDEFT architecture. This offers a promising solution that supports Kubernetes for handling scalable and highly available fog applications with ease while offering CI/CD. FogDEFTKube simplifies the modeling and deployment of fog services while abstracting the complexities of underlying fog networks.
在物联网应用中,传统的以云为中心的方法缺乏时间关键型任务所需的速度和效率,导致网络效率低下。为解决这一问题,边缘计算和雾计算的概念应运而生。雾计算有助于在更靠近网络边缘的地方部署服务和应用,降低延迟并实现实时功能。在网络覆盖不稳定的地区,它还能提高可靠性、容错性和连接性。尽管雾计算克服了以云为中心的物联网处理的局限性,但它的应用也面临着平台独立性、互操作性和可移植性等挑战。为了应对这些挑战,FogDEFT(开箱即用的雾计算:FogDEFT(Fog computing out of the box:Dynamic dEployment of Fog service containers with TOSCA)框架。该框架符合 OASIS-TOSCA 标准,保证在资源受限的设备上动态部署雾服务,同时利用 Docker 容器化技术确保平台独立性和互操作性。由于与专为中型部署而设计的 Docker Swarm 紧密耦合,fogDEFT 框架受到了 Docker Swarm 限制的制约,妨碍了其有效管理大规模、自动化和资源高效型微服务部署的能力。为了解决这些局限性,我们提出了 FogDEFTKube,它是 FogDEFT 架构的扩展,整合了用于协调的 Kubernetes、用于持续集成和部署的 Jenkins 以及对 FogDEFT 架构核心功能的全面重新定义。这提供了一个前景广阔的解决方案,它支持 Kubernetes,可轻松处理可扩展和高可用性的雾应用,同时提供 CI/CD。FogDEFTKube 简化了雾服务的建模和部署,同时抽象了底层雾网络的复杂性。