Fog Computing: Building a Road to IoT with Fog Analytics

There is a great impact on our day-to-day life by integrating platforms of cloud computing and Internet-of-things (IoT). Also, some of the limitations exist in today’s era. Although various services of cloud are freely available and are also comparatively cheaper. But it consumes a large amount of network bandwidth. The main disadvantage of cloud computing is the distance between the data center and the data source. Fog computing offers a solution to these kinds of problems in cloud computing. It is one of the distributed service computing models. It completely utilizes the various computing functions of terminal devices. It also exhibits para-virtualized architecture. The different characteristics of cloud and fog computing platforms are explained in this chapter. Also, the detailed architecture of both platforms is introduced with a comparative analysis. On the fog server, fog analytics tool performs data localization. All the methods of application management such as resource coordination technique, distributed application deployment, and distributed data flow method are discussed. Further, research direction in using Deep Learning to Big Data is detailed as the improved formulation of data abstractions, dimensionality reduction, etc. Also, the possible solutions are presented.

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