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Informationen zum Autor Kai Hwang, PhD is Professor of Electrical Engineering and Computer Science at University of Southern California, USA. He also serves as an EMC-endowed visiting Chair Professor at Tsinghua University, China. He specializes in computer architecture, wireless Internet, cloud computing and network security.Min Chen, PhD is Professor of Computer Science and Technology, Huazhong University of Science and Technology, China. His work focuses on IoT, mobile cloud, body area networks, healthcare big-data and cyber physical systems. Klappentext The definitive guide to successfully integrating social, mobile, big-data analytics, cloud and IoT principles and technologiesThe main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming.Part 1 focuses on data science, the roles of cloud and IoT devices and frameworks for big-data computing. Big-data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big-data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools.* The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies* Covers theory and computing techniques and technologies, making it suitable for use on both computer science and electrical engineering programs* Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies* Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning* Features a companion website with an instructor manual and PowerPoint slidesBig-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculties and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource. Zusammenfassung The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. Inhaltsverzeichnis About the Authors xiPreface xiiiAbout the Companion Website xviiPart 1 Big Data, Clouds and Internet of Things 11. Big Data Science and Machine Intelligence 31.1 Enabling Technologies for Big Data Computing 31.2 Social-Media, Mobile Networks and Cloud Computing 161.3 Big Data Acquisition and Analytics Evolution 241.4 Machine Intelligence and Big Data Applications 321.5 Conclusions 42Homework Problems 42References 432. Smart Clouds, Virtualization and Mashup Services 452.1 Cloud Computing Models and Services 452.2 Creation of Virtual Machines and Docker Containers 572.3 Cloud Architectures and Resources Management 652.4 Case Studies of IaaS, PaaS and SaaS Clouds 772.5 Mobile Clouds and Inter-Cloud Mashup Services 882.6 Conclusions...
