Fog, edge, and pervasive computing in intelligent IoT driven applications / edited by Deepak Gupta, Aditya Khamparia.

Contributor(s): Gupta, Deepak [editor.] | Khamparia, Aditya, 1988- [editor.]
Language: English Publisher: Hoboken, New Jersey : Wiley-IEEE Press, 2020Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781119670100; 9781119670094Subject(s): Internet of things | Cloud computing | Distributed databases | UbIquitous computingGenre/Form: Electronic booksAdditional physical formats: Print version:: Fog, edge, and pervasive computing in intelligent IoT driven applicationsDDC classification: 004.678 LOC classification: TK5105.8857Online resources: Full text available at Wiley Online Library Click here to view Summary: "With the rapid growth and emerging development in artificial technology, novel hybrid and intelligent Internet of Things (IoT), Edge, Fog-driven and Pervasive computing techniques are important part of our daily lives. These technologies utilize in various engineering, industrial, smart farming, video security surveillance, VANETs and vision augmented driven applications. These applications required real time processing of associated data and works on principle of computational resource oriented metaheuristic and machine learning algorithms. As edge/fog computing is implemented at network edges, it promises low latency as well as agile computation augmenting services for device users"-- Provided by publisher.
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004.678 F687 2020 (Browse shelf) Available CL-51224
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Includes bibliographical references and index.

"With the rapid growth and emerging development in artificial technology, novel hybrid and intelligent Internet of Things (IoT), Edge, Fog-driven and Pervasive computing techniques are important part of our daily lives. These technologies utilize in various engineering, industrial, smart farming, video security surveillance, VANETs and vision augmented driven applications. These applications required real time processing of associated data and works on principle of computational resource oriented metaheuristic and machine learning algorithms. As edge/fog computing is implemented at network edges, it promises low latency as well as agile computation augmenting services for device users"-- Provided by publisher.

Description based on print version record and CIP data provided by publisher; resource not viewed.

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