Abstract
With the rapid increase in the number of internet of things (IoT) devices, a huge amount of data is generated which needs proper storage and analytical applications. However, the smart devices do not have adequate resources due to which the applications are mostly supported by cloud servers for providing on-demand and scalable storage as well as computation power using pay-as-you-go model. Despite the broad utilization of cloud computing, few applications such as health monitoring, real-time gaming and emergency response are latency sensitive to be deployed on cloud directly. Therefore, fog computing has emerged as a promising extension to cloud computing paradigm to provide better response time. In fog computing architecture, applications perform pre-processing near to the end user. The combination of fog and cloud can handle big data collection, secure aggregation, and pre-processing, thus reducing the cost of data transportation and storage. For example, in environmental monitoring systems, local data gathered can be aggregated and mined at fog nodes to provide timely feedback especially for emergency cases. The chapter presents the concepts of fog computing along with its characteristics. Furthermore, the chapter elaborates the applications of fog computing in various domains followed by discussion on secure data aggregation methods.
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Rani, S., Saini, P. (2020). Fog Computing: Applications and Secure Data Aggregation. In: Gupta, B., Perez, G., Agrawal, D., Gupta, D. (eds) Handbook of Computer Networks and Cyber Security. Springer, Cham. https://doi.org/10.1007/978-3-030-22277-2_19
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DOI: https://doi.org/10.1007/978-3-030-22277-2_19
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