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

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.

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