Large-Scale Data Streaming in Fog Computing and Its Applications

Large-Scale Data Streaming in Fog Computing and Its Applications

Oshin Sharma (PES University, Bangalore, India) and Anusha S. (School of Engineering and Technology, Jain University, Bangalore, India)
Copyright: © 2021 |Pages: 16
DOI: 10.4018/978-1-7998-3444-1.ch003
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Abstract

The emerging trends in fog computing have increased the interests and focus in both industry and academia. Fog computing extends cloud computing facilities like the storage, networking, and computation towards the edge of networks wherein it offloads the cloud data centres and reduces the latency of providing services to the users. This paradigm is like cloud in terms of data, storage, application, and computation services, except with a fundamental difference: it is decentralized. Furthermore, these fog systems can process huge amounts of data locally and can be installed on hardware of different types. These characteristics make fog suitable for time- and location-based applications like internet of things (IoT) devices which can process large amounts of data. In this chapter, the authors present fog data streaming, its architecture, and various applications.
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Existing Literature

There are many research articles on Fog computing which are published and having applications like smart grid, healthcare, smart city and industrial automation (Lin et al. 2018). The model for fog computing was developed by Sarkar and Misra (Sarkar et al. 2016). wherein a relative performance of cloud computing is analysed with respect to the amount of energy used and latency in service. In the next paper by (Varghese et al. 2017) the viability of Fog computing is analysed and a comparison was done with cloud where the analysis showed that the Fog reduces the average time for response by 20% for each user and the data traffic has got reduced by 90% in the place linking cloud and the edge devices.

Figure 1.

Fog computing: Distributed data processing

978-1-7998-3444-1.ch003.f01

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