Auto-scaling in Kubernetes-Based Fog Computing Platform

Wei Sheng Zheng, Li-Hsing Yen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationNew Trends in Computer Technologies and Applications - 23rd International Computer Symposium, ICS 2018, Revised Selected Papers
EditorsChuan-Yu Chang, Chien-Chou Lin, Horng-Horng Lin
PublisherSpringer Verlag
Pages338-345
Number of pages8
ISBN (Print)9789811391897
DOIs
StatePublished - 1 Jan 2019
Event23rd International Computer Symposium, ICS 2018 - Yunlin, Taiwan
Duration: 20 Dec 201822 Dec 2018

Publication series

NameCommunications in Computer and Information Science
Volume1013
ISSN (Print)1865-0929

Conference

Conference23rd International Computer Symposium, ICS 2018
CountryTaiwan
CityYunlin
Period20/12/1822/12/18

Keywords

  • Container
  • Fog computing
  • Kubernetes
  • Scalability

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