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Container-Based Virtualization for Real-Time Data Streaming Processing on the Edge Computing Architecture

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Abstract

Container-based virtualization is one of the prominent technologies in the cloud computing. Containers virtualize at the operating system level which provides a lightweight operation than traditional virtualization on a hypervisor. The combination of the Internet of Things (IoT), edge computing and container-based virtualization is going to make system rapid, inexpensive, and more reliable. In this paper, we intend to implement a complete set of edge computing architectures based on containerization on an IoT environment. In this case, we implemented container-based virtualization which constructs Kubernetes Minion (Nodes) in the Docker container service independently for each service on the Edge side. We used humidity and temperature sensory data as our case study. We set up the Raspberry Pi on the Edge Gateway and Kubernetes minion on the Raspberry Pi to provide the service application, which contains Grafana, the open platform for analytics and monitoring. For short-term data storage, we use InfluxDB as a data store for large amounts of time-series data.

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Acknowledgment

This work was supported in part by the Ministry of Science and Technology, Taiwan R.O.C., under grants number 107-2221-E-029-008-.

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Correspondence to Chao-Tung Yang .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Kristiani, E., Yang, CT., Wang, YT., Huang, CY., Ko, PC. (2019). Container-Based Virtualization for Real-Time Data Streaming Processing on the Edge Computing Architecture. In: Chen, JL., Pang, AC., Deng, DJ., Lin, CC. (eds) Wireless Internet. WICON 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-030-06158-6_21

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  • DOI: https://doi.org/10.1007/978-3-030-06158-6_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-06157-9

  • Online ISBN: 978-3-030-06158-6

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