Intelligent network design driven by big data analytics, IoT, AI and cloud computing

As enterprise access networks evolve with a larger number of mobile users, a wide range of devices and new cloud-based applications, managing user performance on an end-to-end basis has become rather challenging. Recent advances in big data network analytics combined with AI and cloud computing are...

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Bibliographic Details
Other Authors: Kumar, Sunil (College teacher), (Editor), Mapp, Glenford, (Editor), Cengiz, Korhan, (Editor)
Format: eBook
Language: English
Published: Stevenage : Institution of Engineering & Technology, 2022
Subjects:
ISBN: 9781839535345
1839535342
9781839535338
1839535334
Physical Description: 1 online resource (551 pages) : illustrations

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Summary: As enterprise access networks evolve with a larger number of mobile users, a wide range of devices and new cloud-based applications, managing user performance on an end-to-end basis has become rather challenging. Recent advances in big data network analytics combined with AI and cloud computing are being leveraged to tackle this growing problem. AI is becoming further integrated with software that manage networks, storage, and can compute. This edited book focuses on how new network analytics, IoTs and Cloud Computing platforms are being used to ingest, analyse and correlate a myriad of big data across the entire network stack in order to increase quality of service and quality of experience (QoS/QoE) and to improve network performance. From big data and AI analytical techniques for handling the huge amount of data generated by IoT devices, the authors cover cloud storage optimization, the design of next generation access protocols and internet architecture, fault tolerance and reliability in intelligent networks, and discuss a range of emerging applications. This book will be useful to researchers, scientists, engineers, professionals, advanced students and faculty members in ICTs, data science, networking, AI, machine learning and sensing. It will also be of interest to professionals in data science, AI, cloud and IoT start-up companies, as well as developers and designers.
Bibliography: Includes bibliographical references and an index.
ISBN: 9781839535345
1839535342
9781839535338
1839535334
Access: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty