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Full Description
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.
Contents
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
