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Performance and Scalability Improvement Using IoT-Based Edge Computing Container Technologies

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Abstract

Different containers support multiple applications on multiple disciplines according to technological needs. They improve the need of multitasking activities and are used to support and combine work with different paradigms, technologies, disciplines and application orientations. It increases the user requirements and the system requirements. It might be extended based on the needs of specifications. Like this idea support from to the container which specifies the application onto it, and performs the self-organizing things for an enhancement. In this paper, container technology is proposed for Internet of Things (IoT) and Fog of Things (FoT) enabled devices for plethora FoT servers to serve SOFT for each application through the gateways to available devices. The fog is not only for the data processing and storage management. It can also keep with the IoT services by through the FoT server in distributed manner. The main aim of this paper is to examine the ability to scale an IoT system using multiple container technologies with clusters managements. With the use of this approach, the number of connected devices can be increased and network efficiency is improved for better computation, control and data storage.

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Acknowledgements

We would like to thank all the reference authors for providing access to the information and images on their IoT environment.

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Authors and Affiliations

  1. A.V.C. College of Engineering, Mannampandal, Mayiladuthurai, India

    K. Aruna

  2. Department of Computer Applications, A.V.C. College of Engineering, Mannampandal, Mayiladuthurai, India

    G. Pradeep

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  1. K. Aruna
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  2. G. Pradeep
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Correspondence to K. Aruna.

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This article is part of the topical collection “Advances in Computational Intelligence, Paradigms and Applications” guest edited by Young Lee and S. Meenakshi Sundaram.

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Aruna, K., Pradeep, G. Performance and Scalability Improvement Using IoT-Based Edge Computing Container Technologies. SN COMPUT. SCI. 1, 91 (2020). https://doi.org/10.1007/s42979-020-0106-9

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  • DOI: https://doi.org/10.1007/s42979-020-0106-9

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