Node-Based Horizontal Pod Autoscaler in KubeEdge-Based Edge Computing Infrastructure

Abstract

KubeEdge (KE) is a container orchestration platform for deploying and managing containerized IoT applications in an edge computing environment based on Kubernetes. It is intended to be hosted at the edge and provides seamless cloud-edge coordination as well as an offline mode that allows the edge to function independently of the cloud. However, there are unreliable communication links between edge nodes in edge computing environments, implying that load balancing in an edge computing environment is not guaranteed while using KE. Furthermore, KE lacks Horizontal Pod Autoscaling (HPA), implying that KE cannot dynamically deploy new resources to efficiently handle increasing requests. Both of the aforementioned issues have a significant impact on the performance of the KE-based edge computing system, particularly when traffic volumes vary over time and geographical location. In this study, a node-based horizontal pod autoscaler (NHPA) is proposed to provide dynamical adjustment for the number of pods of individual nodes independently from each other in an edge computing environment where the traffic volume fluctuates over time and location, and the communication links between edge nodes are not stable. The proposed NHPA can dynamically adjust the number of pods depending on the incoming traffic at each node, which will improve the overall performance of the KubeEdge-based edge computing environment. In the KubeEdge-based edge computing environment, the experimental findings reveal that NHPA outperforms KE in terms of throughput and response time by a factor of about 3 and 25, respectively.

Keywords

• Kubernetes
• KubeEdge
• horizontal pod autoscaler
• dynamic resource provisioning
• edge computing
• IoT