Abstract
Edge clusters consisting of small and affordable single-board devices are used in a range of different applications such as microcontrollers regulating an industrial process or controllers monitoring and managing traffic roadside. We call this wider context of computational infrastructure between the sensor and Internet-of-Things world and centralised cloud data centres the edge or edge computing. Despite the growing hardware capabilities of edge devices, resources are often still limited and need to be used intelligently. This can achieved by providing a self-adaptive scaling component in these clusters that is capable of scaling individual parts of the application running in the cluster. We propose an auto-scalable container-based cluster architecture for lightweight edge devices. A serverless architecture is at the core of the management solution. Our auto-scaler as the key component of this architecture is based on fuzzy logic in order to address challenges arising from an uncertain environment. In this context, it is crucial to evaluate the capabilities and limitations of the application in a real-world context. Our results show that the proposed platform architecture, the implemented application and the scaling functionality meet the set requirements and offer a basis for lightweight edge computing.