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Title	Edge/Fog Computing Paradigm: Concept, Platforms And Toolchains
ID_Doc	21853
Authors	Krishnaraj N.; Daniel A.; Saini K.; Bellam K.
Year	2022
Published	Advances in Computers, 127
DOI	http://dx.doi.org/10.1016/bs.adcom.2022.02.012
Abstract	At the moment, Web applications operating on smart phones create huge amounts of data that may be processed on the Cloud. Yet, one of a Cloud's core limitations is its connection to endpoint devices. Through the use of distributed compute, communication, and storage services along the Cloud to Things (C2T) continuum, fog computing overcomes this constraint and empowers new application possibilities such as smart cities, augmented reality (AR), and virtual reality (VR) (VR). Furthermore, the use of Fog-based computing resources and its incorporation with the Cloud brings new resource management issues, necessitating the development of new techniques to ensure application quality of service (QoS) compliance. In this setting, a critical challenge is how to link application QoS needs to Fog and Cloud resources. One possibility is to classify the applications that arrive at the Fog into Classes of Service (CoS). Thus, this article provides a set of CoS for fog applications that incorporates the QoS criteria that most accurately describe these fog applications. Additionally, this article suggests the use of a standard machine learning classification approach to differentiate Fog computing applications based on their QoS needs. Additionally, this technique is demonstrated through the evaluation of classifiers' efficiency, accuracy, and robustness to noise. Adopting a technique for machine learning-based categorization is a first step in defining methods for providing QoS in fog computing. Additionally, categorizing Fog computing applications can aid the Fog scheduler's decision-making process. © 2022 Elsevier Inc.
Author Keywords	Cloud computing; Edge computing; Fog computing; Internet of things; Mobility analytics; Security

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