Auto Scaling in k8s-based Fog Computing Platform

• Main Authors: Zheng, Wei Sheng, 鄭偉聖
• Other Authors: 嚴力行
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/cf8gs8

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 106 === Software virtualization, the kernel of cloud computing, benefits the emerging Inter of Things (IoT) applications by providing virtualized computing platform in the cloud. However, with increasing demands of low response latency, there has been a trend of moving computing platform to the edge of network, a new computation 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. Real experiments have been conducted to investigate the performance of the proposed scheme. The results show that the performance improvement and fog platform resource can be balance, fitness between resource usage and application instances.