This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka and so forth. It also covers developments in big data computing applications such as Machine Learning, Deep Learning, Graph Processing, and many others. Features: · Provides comprehensive analysis of advanced aspects on big data challenges and enabling technologies. · Explains computing models are explained using real world examples and dataset based experiments. · Includes case studies, quality diagrams and demonstrations in each chapter. · Describes modifications and optimization of existing technologies along with the novel big data computing models. · Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high performance computing, data mining and knowledge discovery, and distributed computing.

Discusses the requirements and establishment of a layered protocol architecture. Highlights the importance of cable media in getting a high-speed network. Covers the fundamental concepts and advanced topics such as metro ethernet, and ethernet first mile in the field of networking. Presents important topics such as multiprotocol label switching, cloud computing in networking, and the internet of things. Explores the necessity of software-defined networking and network functions virtualization.