Resource management is the principal factor to fully utilize the potential of Edge/Fog computing to execute real-time and critical IoT applications. Although some resource management frameworks exist, the majority are not designed based on distributed containerized components. Hence, they are not suitable for highly distributed and heterogeneous computing environments. Containerized resource management frameworks such as FogBus2 enable efficient distribution of framework's components alongside IoT applications' components. However, the management, deployment, health-check, and scalability of a large number of containers are challenging issues. To orchestrate a multitude of containers, several orchestration tools are developed. But, many of these orchestration tools are heavy-weight and have a high overhead, especially for resource-limited Edge/Fog nodes. Thus, for hybrid computing environments, consisting of heterogeneous Edge/Fog and/or Cloud nodes, lightweight container orchestration tools are required to support both resource-limited resources at the Edge/Fog and resource-rich resources at the Cloud. Thus, in this paper, we propose a feasible approach to build a hybrid and lightweight cluster based on K3s, for the FogBus2 framework that offers containerized resource management framework. This work addresses the challenge of creating lightweight computing clusters in hybrid computing environments. It also proposes three design patterns for the deployment of the FogBus2 framework in hybrid environments, including 1) Host Network, 2) Proxy Server, and 3) Environment Variable. The performance evaluation shows that the proposed approach improves the response time of real-time IoT applications up to 29% with acceptable and low overhead.
翻译:资源管理是充分利用Edge/Fog计算潜力实施实时和关键的IoT应用程序的主要因素。虽然存在一些资源管理框架,但大部分不是基于分布式集装箱组件设计的,因此不适合高度分布和多样化的计算环境。FogBus2等封闭式资源管理框架使得框架组件与IoT应用程序组件一起能够高效分布。然而,大量集装箱的管理、部署、健康检查和可缩放都是具有挑战性的问题。为协调大量集装箱,开发了若干管弦工具。但是,许多这些管弦工具都是超重和高顶部的,特别是资源有限的Edge/Fog节点。因此,对于混合计算环境,包括混成的Edge/Fog和/或Cloud节点,需要轻量的集装箱调调控工具来支持Edge/Fog/Fog/Fog的拟议资源有限性资源。因此,我们建议采用一种可行的方法,在K3的服务器上构建一个混合和轻量的集束集束组合。对于Fog-breal2的运行环境来说,它也提出了一种简化的计算环境设计框架。