Big Data Management and Processing 1st edition by Kuan-Ching Li – Ebook PDF Instand Download/DeliveryISBN: 1351650041, 9781351650045
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Product details:
ISBN-10 : 1351650041
ISBN-13 : 9781351650045
Author: Kuan-Ching Li
From the Foreword: “Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications… [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies.” —Sartaj Sahni, University of Florida, USA “Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided.
Big Data Management and Processing 1st Table of contents:
Chapter 1: Big Data: Legal Compliance and Quality Management
Chapter 2: Energy Management for Green Big Data Centers
Chapter 3: The Art of In-Memory Computing for Big Data Processing
Chapter 4: Scheduling Nested Transactions on In-Memory Data Grids
Chapter 5: Co-Scheduling High-Performance Computing Application
Chapter 6: Resource Management for MapReduce Jobs Performing Big Data Analytics
Chapter 7: Tyche: An Efficient Ethernet-Based Protocol for Converged Networked Storage
Chapter 8: Parallel Backpropagation Neural Network for Big Data Processing on Many-Core Platform
Chapter 9: SQL-on-Hadoop Systems: State-of-the-Art Exploration, Models, Performances, Issues, and Recommendations
Chapter 10: One Platform Rules All: From Hadoop 1.0 to Hadoop 2.0 and Spark
Chapter 11: Security, Privacy, and Trust for User-Generated Content: The Challenges and Solutions
Chapter 12: Role of Real-Time Big Data Processing in the Internet of Things
Chapter 13: End-to-End Security Framework for Big Sensing Data Stream
Chapter 14: Considerations on the Use of Custom Accelerators for Big Data Analytics
Chapter 15: Complex Mining from Uncertain Big Data in Distributed Environments: Problems, Definitions, and Two Effective and Efficient Algorithms
Chapter 16: Clustering in Big Data
Chapter 17: Large Graph Computing Systems
Chapter 18: Big Data in Genomic
Chapter 19: Maximizing the Return on Investment in Big Data Projects: An Approach Based upon the Incremental Funding of Project Developmen
Chapter 20: Parallel Data Mining and Applications in Hospital Big Data Processin
Chapter 21: Big Data in the Parking Lot
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