Abstract
Traditional cloud computing has the challenge to serve many clients with many services. Spreading the services to across of edge server will reduce the load of traditional cloud computing. Kubernetes is one of the platforms used for cloud management. Kubernetes helps to deploy, and scaling the application. Nowadays, a lot of communities build a lightweight Kubernetes than suitable for edge device such as Raspberry Pi. This paper Investigate the performance of Kubernetes lightweight that installed in the Raspberry Pi.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Huang, Y., Cai, K., Zong, R., Mao, Y.: Design and implementation of an edge computing platform architecture using Docker and Kubernetes for machine learning, pp. 29–32 (2019)
Wang, P., Liu, S., Ye, F., Chen, X.: A Fog-based Architecture and Programming Model for IoT Applications in the Smart Grid (2018)
Li, C., Sun, H., Chen, Y., Luo, Y.: Edge cloud resource expansion and shrinkage based on workload for minimizing the cost. Futur. Gener. Comput. Syst. 101, 327–340 (2019)
Cappos, J., Rafetseder, A., Hemmings, M., McGeer, R., Ricart, G.: EdgeNet: a global cloud that spreads by local action. In: Proceedings - 2018 3rd ACM/IEEE Symposium Edge Computer SEC 2018, pp. 359–360 (2018)
Eiermann, A., Renner, M., GroBmann, M.: On a Fog Computing Platform Built on ARM Architectures by Docker Container Technology, vol. 863, pp. 71–86 (2018)
Santoro, D., Zozin, D., Pizzolli, D., De Pellegrini, F., Cretti, S.: Foggy: a platform for workload orchestration in a fog computing environment. In: Proceedings International Conference Cloud Computing Technology Science CloudCom, vol. 2017-December, pp. 231–234 (2017)
Mittermeier, L., Katenbrink, F., Seitz, A., Muller, H., Bruegge, B.: Dynamic scheduling for seamless computing. In: Proceedings - 8th IEEE International Symposium Cloud Service Computing SC2 2018, pp. 41–48 (2018)
Abdollahi Vayghan, L., Saied, M.A., Toeroe, M., Khendek, F.: Deploying microservice based applications with kubernetes: experiments and lessons learned. IEEE Int. Conf. Cloud Comput. CLOUD 2018, 970–973 (2018)
Xiong, Y., Sun, Y., Xing, L., Huang, Y.: Extend cloud to edge with KubeEdge. In: Proceedings - 2018 3rd ACM/IEEE Symposium Edge Computing SEC 2018, pp. 373–377 (2018)
“K3S”. http://k3s.io. Accessed 09 July 2019
“KubeEdge”. http://KubeEdge.io. Accessed 09 July 2019
DockerHub. https://hub.docker.com/u/richardchesterwood. 30 June 2019
“Kubernetes”. https://kubernetes.io/blog/2019/03/19/kubeedge-k8s-based-edge-intro/. 09 July 2019
“RancherOS”. https://rancher.com/rancher-os/. Accessed 09 July 2019
Chang, C., Yang, S., Yeh, E., Lin, P., Jeng, J.: A kubernetes-based monitoring platform for dynamic cloud resource provisioning. In: GLOBECOM 2017 - 2017 IEEE Global Communications Conference, pp. 1–6. Singapore (2017)
Sharma, P., Chaufournier, L., Shenoy, P., Tay, Y.C.: Containers and virtual machines at scale: a comparative study. In: Proceedings of the 17th International Middleware Conference (Middleware 2016), p. 13. ACM, New York, NY, USA, Article 1 (2016)
Acknowledgment
This work is supported in part by the Ministry of Science and Technology, Taiwan, ROC, under grant number MOST 108-2622-8-029-004-TM1, MOST 108-2221-E-029-010, MOST 106-2221-E-164-009-MY2 and MOST 108-2221-E-126-002.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Fathoni, H., Yang, CT., Chang, CH., Huang, CY. (2019). Performance Comparison of Lightweight Kubernetes in Edge Devices. In: Esposito, C., Hong, J., Choo, KK. (eds) Pervasive Systems, Algorithms and Networks. I-SPAN 2019. Communications in Computer and Information Science, vol 1080. Springer, Cham. https://doi.org/10.1007/978-3-030-30143-9_25
Download citation
DOI: https://doi.org/10.1007/978-3-030-30143-9_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30142-2
Online ISBN: 978-3-030-30143-9
eBook Packages: Computer ScienceComputer Science (R0)