Conveying the workload of IoT systems from the cloud to edge nodes have been widely adopted by industrial and academic sectors. This tendency is generally promoted to meet the requirements of some time-sensitive use cases such as IoT healthcare applications. However, IoT devices at the edge network are likely to be resource-limited, as well as, they perform under an extremely heterogeneous environment in terms of the connected devices and the deployed software modules. Thus, both of the aforementioned concerns have considerably led to hindering the deployment process of services on IoT edge devices. In this paper, we propose an approach to facilitate a scalable and lightweight solution for service deployment for efficient resource utilization on IoT edge nodes. Our solution is based on the container concept, and we adopt the cluster concept to define a group of IoT edge devices. Containers are lightweight virtualization technique that enables services to be packaged and deployed with their dependencies regardless of the hosts infrastructure, as well as, they facilitate the service communication and the update process. Furthermore, containers are supported by some means of orchestration such as swarm. These orchestration tools can be configured to enable services deployment and resources sharing among IoT edge devices falling within the same cluster. However, they lack elasticity in terms of auto-scaling up/down of services instances in corresponding to the resource utilization of all cluster elements, as well as, service performance metrics. Our approach overcomes these limitations by following an auto-scaling process based on MAPE-K loop, which is based on our proposed rule model to generate a scaling plan by analyzing collected performance metrics of a cluster. Our evaluation shows the efficiency of the proposed approach in adapting the system performance to meet service performance requirements and the availability of system resources.

将物联网系统的工作负载从云传输到边缘节点已被工业和学术界广泛采用。通常会促进这种趋势以满足某些时间敏感型用例的需求，例如IoT医疗保健应用程序。但是，边缘网络上的IoT设备很可能会受到资源的限制，并且它们在连接设备和已部署软件模块的异构环境下运行。因此，上述两个问题都极大地阻碍了物联网边缘设备上服务的部署过程。在本文中，我们提出了一种方法，以促进可扩展的轻量级服务部署解决方案，以在IoT边缘节点上高效利用资源。我们的解决方案基于容器的概念，我们采用集群概念来定义一组物联网边缘设备。容器是轻量级的虚拟化技术，它使服务可以依赖于它们的依赖关系进行打包和部署，而与主机基础结构无关，并且它们可以促进服务通信和更新过程。此外，通过诸如编组之类的编排来支撑容器。可以将这些编排工具配置为在同一群集内的IoT边缘设备之间实现服务部署和资源共享。但是，它们在与所有群集元素的资源利用率以及服务性能指标相对应的服务实例的自动扩展/缩减方面缺乏弹性。我们的方法通过遵循基于MAPE-K循环的自动缩放过程来克服这些限制，它基于我们提出的规则模型，通过分析收集的集群性能指标来生成扩展计划。我们的评估表明，该方法在调整系统性能以满足服务性能要求和系统资源可用性方面的效率。