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From Cloud Computing to Fog Computing: Platforms for the Internet of Things (IoT)

From Cloud Computing to Fog Computing: Platforms for the Internet of Things (IoT)
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Author(s): Sanjay P. Ahuja (School of Computing, University of North Florida, Jacksonville, FL, USA)and Niharika Deval (School of Computing, University of North Florida, Jacksonville, FL, USA)
Copyright: 2021
Pages: 12
Source title: Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-5339-8.ch047

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Abstract

This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.

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