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Fog Resource Allocation Through Machine Learning Algorithm

Fog Resource Allocation Through Machine Learning Algorithm
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Author(s): Gowri A. S. (Pondicherry University, India) and Shanthi Bala P. (Pondicherry University, India)
Copyright: 2020
Pages: 41
Source title: Architecture and Security Issues in Fog Computing Applications
Source Author(s)/Editor(s): Sam Goundar (The University of the South Pacific, Fiji), S. Bharath Bhushan (Sree Vidyanikethan Engineering College, India) and Praveen Kumar Rayani (National Institute of Technology, Durgapur, India)
DOI: 10.4018/978-1-7998-0194-8.ch001


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Internet of things (IoT) prevails in almost all the equipment of our daily lives including healthcare units, industrial productions, vehicle, banking or insurance. The unconnected dumb objects have started communicating with each other, thus generating a voluminous amount of data at a greater velocity that are handled by cloud. The requirements of IoT applications like heterogeneity, mobility support, and low latency form a big challenge to the cloud ecosystem. Hence, a decentralized and low latency-oriented computing paradigm like fog computing along with cloud provide better solution. The service quality of any computing model depends on resource management. The resources need to be agile by nature, which clearly demarks virtual container as the best choice. This chapter presents the federation of Fog-Cloud and the way it relates to the IoT requirements. Further, the chapter deals with autonomic resource management with reinforcement learning (RL), which will forward the fog computing paradigm to the future generation expectations.

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