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Fog and Edge Computing

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Abstract

Thanks to innovations like the Internet of Things and autonomous driving, millions of new devices, sensors, and applications will be going online in the near future. They will generate huge amounts of data, which connected technologies will have to be able to handle. Measuring, monitoring, analyzing, processing, and reacting are just a few examples of tasks involving the vast quantities of data that these devices, sensors, and applications will generate. Existing models like cloud computing are reaching their limits and will struggle to cope with this deluge of data. This chapter introduces fog and edge computing as a model in which computing power moves toward the sources where the data are generated. Following a brief definition and overview of fog and edge computing, eight of their unique characteristics are described, including contextual location awareness and low latency. Differences between this model and the better-known cloud computing model, as well as other related models, are also explained, and the challenges and opportunities of fog and edge computing are discussed. In addition to the definition and characteristics of fog and edge computing, examples of practical implementation are presented.

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Further Reading

  • Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the Internet of things. In: Paper presented at the first edition of the MCC workshop on Mobile cloud computing, Helsinki, Finland, 17 August 2012

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  • Mahmood Z (2018) Fog computing: concepts, frameworks and technologies, 1st edn. Springer, Cham, Switzerland

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  • Yi S, Qin Z, Li Q (2015) Security and privacy issues of fog computing: a survey. In: Paper presented at the international conference on wireless algorithms, systems, and applications, Qufu, China, 10–12 August 2015

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  1. Institute of Applied Informatics and Formal Description Methods, Karlsruhe Institute of Technology, Karlsruhe, Germany

    Ali Sunyaev

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Sunyaev, A. (2024). Fog and Edge Computing. In: Internet Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-61014-1_7

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  • DOI: https://doi.org/10.1007/978-3-031-61014-1_7

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