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Intelligent Network Design Driven by Big Data Analytics, IoT, AI and Cloud Computing

Kumar Sunil Mapp Glenford Cengiz, Korhan
Innbundet / 2022 / Engelsk

Produktdetaljer

ISBN
9781839535338
Publisert
2022-11-10
Utgiver
Vendor
Institution of Engineering and Technology
Høyde
234 mm
Bredde
156 mm
Aldersnivå
P, UP, UU, 06, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
427

Redaktør
Kumar Sunil
Mapp Glenford
Cengiz, Korhan

Om bidragsyterne

Sunil Kumar is an associate professor of Computer Science and Engineering at Amity University, Noida campus, India. His research interests include computer networks, distributed systems, wireless sensor networks, SDN, and big data. He is industry CCNA & CCNP certified. He is a member of the IET, CSTA, IAER, IAENG. He holds a PhD in energy optimization in distributed wireless sensor networks from Amity University, Noida India. Glenford Mapp is an associate professor at Middlesex University, London, UK. His primary expertise is in the development of new technologies for mobile and distributed systems such as service platforms, cloud computing, network addressing and transport protocols for local environments. He had previously worked for AT&T Cambridge Laboratories for ten years. He received his PhD in computer science from the University of Cambridge, UK. Korhan Cengiz is an assistant professor of electrical and electronics engineering at Trakya University, Turkey. His research interests include computer networks, big data, wireless sensor networks, wireless communications, routing protocols, statistical signal processing, indoor positioning systems, power electronics and machine learning. He is an associate editor of Interdisciplinary Sciences: Computational Life Sciences, handling editor of Microprocessors and Microsystems, and associate editor of IET Electronics Letters, IET Networks, amongst others.

Intelligent Network Design Driven by Big Data Analytics, IoT, AI and Cloud Computing

Kumar Sunil Mapp Glenford Cengiz, Korhan
Innbundet / 2022 / Engelsk
Kumar Sunil Mapp Glenford Cengiz, Korhan
Innbundet / 2022 / Engelsk
Nettpris:
1.885,-
Levering 7-20 dager
Sjekk lagerstatus i butikk
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.
Les mer
This book shows how innovations in 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.
Les mer
Chapter 1: Introduction to intelligent network design driven by big data analytics, IoT, AI and cloud computingChapter 2: Role of automation, Big Data, AI, ML IBN, and cloud computing in intelligent networksChapter 3: An intelligent verification management approach for efficient VLSI computing systemChapter 4: Evaluation of machine learning algorithms on academic big dataset by using feature selection techniquesChapter 5: Accurate management and progression of Big Data AnalysisChapter 6: Cram on data recovery and backup cloud computing techniquesChapter 7: An adaptive software-defined networking (SDN) for load balancing in cloud computingChapter 8: Emerging security challenges in cloud computing: an insightChapter 9: Factors responsible and phases of speaker recognition systemChapter 10: IoT-based water quality assessment using fuzzy logic controllerChapter 11: Design and analysis of wireless sensor network for intelligent transportation and industry automationChapter 12: A review of edge computing in healthcare Internet of things: theories, practices and challengesChapter 13: Image Processing for medical images on the basis of intelligence and biocomputingChapter 14: IoT-based architecture for smart health-care systemsChapter 15: IoT-based heart disease prediction systemChapter 16: DIAIF: Detection of Interest Flooding using Artificial Intelligence-based Framework in NDN androidChapter 17: Intelligent and cost-effective mechanism for monitoring road quality using machine learningChapter 18: Conclusion
Les mer

Relaterte produkter

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.
Les mer
This book shows how innovations in 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.
Les mer
Chapter 1: Introduction to intelligent network design driven by big data analytics, IoT, AI and cloud computingChapter 2: Role of automation, Big Data, AI, ML IBN, and cloud computing in intelligent networksChapter 3: An intelligent verification management approach for efficient VLSI computing systemChapter 4: Evaluation of machine learning algorithms on academic big dataset by using feature selection techniquesChapter 5: Accurate management and progression of Big Data AnalysisChapter 6: Cram on data recovery and backup cloud computing techniquesChapter 7: An adaptive software-defined networking (SDN) for load balancing in cloud computingChapter 8: Emerging security challenges in cloud computing: an insightChapter 9: Factors responsible and phases of speaker recognition systemChapter 10: IoT-based water quality assessment using fuzzy logic controllerChapter 11: Design and analysis of wireless sensor network for intelligent transportation and industry automationChapter 12: A review of edge computing in healthcare Internet of things: theories, practices and challengesChapter 13: Image Processing for medical images on the basis of intelligence and biocomputingChapter 14: IoT-based architecture for smart health-care systemsChapter 15: IoT-based heart disease prediction systemChapter 16: DIAIF: Detection of Interest Flooding using Artificial Intelligence-based Framework in NDN androidChapter 17: Intelligent and cost-effective mechanism for monitoring road quality using machine learningChapter 18: Conclusion
Les mer

Produktdetaljer

ISBN
9781839535338
Publisert
2022-11-10
Utgiver
Vendor
Institution of Engineering and Technology
Høyde
234 mm
Bredde
156 mm
Aldersnivå
P, UP, UU, 06, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
427

Redaktør
Kumar Sunil
Mapp Glenford
Cengiz, Korhan

Om bidragsyterne

Sunil Kumar is an associate professor of Computer Science and Engineering at Amity University, Noida campus, India. His research interests include computer networks, distributed systems, wireless sensor networks, SDN, and big data. He is industry CCNA & CCNP certified. He is a member of the IET, CSTA, IAER, IAENG. He holds a PhD in energy optimization in distributed wireless sensor networks from Amity University, Noida India. Glenford Mapp is an associate professor at Middlesex University, London, UK. His primary expertise is in the development of new technologies for mobile and distributed systems such as service platforms, cloud computing, network addressing and transport protocols for local environments. He had previously worked for AT&T Cambridge Laboratories for ten years. He received his PhD in computer science from the University of Cambridge, UK. Korhan Cengiz is an assistant professor of electrical and electronics engineering at Trakya University, Turkey. His research interests include computer networks, big data, wireless sensor networks, wireless communications, routing protocols, statistical signal processing, indoor positioning systems, power electronics and machine learning. He is an associate editor of Interdisciplinary Sciences: Computational Life Sciences, handling editor of Microprocessors and Microsystems, and associate editor of IET Electronics Letters, IET Networks, amongst others.

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