Auto-scaling in Kubernetes-Based Fog Computing Platform

Cloud computing benefits emerging Inter of Things (IoT) applications by providing virtualized computing platform in the cloud. However, increasing demands of low-latency services motivates the placement of computing platform on the edge of network, a new computing paradigm named fog computing. This study assumes container as virtualized computing platform and uses Kubernetes to manage and control geographically distributed containers. We consider the design and implementation of an auto-scaling scheme in this environment, which dynamically adjusts the number of application instances to strike a balance between resource usage and application performance. The key components of the implementation include a scheme to monitor load status of physical hosts, an algorithm that determines the appropriate number of application instances, and an interface to Kubernetes to perform the adjustment. Experiments have been conducted to investigate the performance of the proposed scheme. The results confirm the effectiveness of the proposed scheme in reducing application response time.