Introduction to Fog Data Analytics for IoT Applications

Abstract

Dictionary meaning of FOG: Vaporized condensed fine particles of water spread in the lower atmosphere that differs from cloud only in being near the ground. Fog Computing actually works almost the same way as its dictionary meaning. The term Fog computing was coined by Cisco Systems Inc., which later formed a Consortium named “OpenFog consortium”, with other high tech companies and academic institutions around the world aimed at the standardization and promotion of fog computing (Bonomi et al. in Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing-MCC ’12, Helsinki, Finland, pp. 13–15 [1]). Fog computing is an extension of cloud computing, which helps in strengthening the cloud paradigm. Cloud is the backbone for IoT devices. According to Gartner, Inc., 20.4 billion connected things will be in use worldwide by 2020. All these devices will produce huge amounts of hot data that need to be processed quickly. Fog computing brings cloud closer to IoT devices and provides real-time processing of data. Fog computing in the IoT also helps in improving efficiency, performance and reduces the amount of data transferred to cloud for processing, data analysis, and storage. We will see in this chapter, the role of fog computing to improve IoT/cloud paradigm. This chapter introduces you to the Genesis of fog computing, Role of fog computing in IoT applications, why to use fog computing, Architecture of fog computing, how fog computing works, fog nodes, Characteristics of fog computing, Comparing Fog computing with cloud computing, difference between fog and edge computing, Advantages and disadvantage of fog computing, and applications of fog computing. After studying this chapter, you will become familiar with the overall concept of fog computing in the context of IoT applications.