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Index
Cover image
Title page
Table of Contents
Copyright
List of contributors
About the Editors
Preface
Organization of the Book
Part I: Big Data Science
Part II: Big Data Infrastructures and Platforms
Part III: Big Data Security and Privacy
Part IV: Big Data Applications
Acknowledgments
Part I: Big Data Science
Chapter 1: Big Data Analytics = Machine Learning + Cloud Computing
Abstract
1.1 Introduction
1.2 A Historical Review of Big Data
1.3 Historical Interpretation of Big Data
1.4 Defining Big Data From 3Vs to 32Vs
1.5 Big Data Analytics and Machine Learning
1.6 Big Data Analytics and Cloud Computing
1.7 Hadoop, HDFS, MapReduce, Spark, and Flink
1.8 ML + CC → BDA and Guidelines
1.9 Conclusion
Chapter 2: Real-Time Analytics
Abstract
2.1 Introduction
2.2 Computing Abstractions for Real-Time Analytics
2.3 Characteristics of Real-Time Systems
2.4 Real-Time Processing for Big Data — Concepts and Platforms
2.5 Data Stream Processing Platforms
2.6 Data Stream Analytics Platforms
2.7 Data Analysis and Analytic Techniques
2.8 Finance Domain Requirements and a Case Study
2.9 Future Research Challenges
Chapter 3: Big Data Analytics for Social Media
Abstract
Acknowledgments
3.1 Introduction
3.2 NLP and Its Applications
3.3 Text Mining
3.4 Anomaly Detection
Chapter 4: Deep Learning and Its Parallelization
Abstract
4.1 Introduction
4.2 Concepts and Categories of Deep Learning
4.3 Parallel Optimization for Deep Learning
4.4 Discussions
Chapter 5: Characterization and Traversal of Large Real-World Networks
Abstract
Acknowledgments
5.1 Introduction
5.2 Background
5.3 Characterization and Measurement
5.4 Efficient Complex Network Traversal
5.5 k-Core-Based Partitioning for Heterogeneous Graph Processing
5.6 Future Directions
5.7 Conclusions
Part II: Big Data Infrastructures and Platforms
Chapter 6: Database Techniques for Big Data
Abstract
6.1 Introduction
6.2 Background
6.3 NoSQL Movement
6.4 NoSQL Solutions for Big Data Management
6.5 NoSQL Data Models
6.6 Future Directions
6.7 Conclusions
Chapter 7: Resource Management in Big Data Processing Systems
Abstract
7.1 Introduction
7.2 Types of Resource Management
7.3 Big Data Processing Systems and Platforms
7.4 Single-Resource Management in the Cloud
7.5 Multiresource Management in the Cloud
7.6 Related Work on Resource Management
7.7 Open Problems
7.8 Summary
Chapter 8: Local Resource Consumption Shaping: A Case for MapReduce
Abstract
8.1 Introduction
8.2 Motivation
8.3 Local Resource Shaper
8.4 Evaluation
8.5 Related Work
8.6 Conclusions
Appendix CPU Utilization With Different Slot Configurations and LRS
Chapter 9: System Optimization for Big Data Processing
Abstract
9.1 Introduction
9.2 Basic Framework of the Hadoop Ecosystem
9.3 Parallel Computation Framework: MapReduce
9.4 Job Scheduling of Hadoop
9.5 Performance Optimization of HDFS
9.6 Performance Optimization of HBase
9.7 Performance Enhancement of Hadoop System
9.8 Conclusions and Future Directions
Chapter 10: Packing Algorithms for Big Data Replay on Multicore
Abstract
10.1 Introduction
10.2 Performance Bottlenecks
10.3 The Big Data Replay Method
10.4 Packing Algorithms
10.5 Performance Analysis
10.6 Summary and Future Directions
Part III: Big Data Security and Privacy
Chapter 11: Spatial Privacy Challenges in Social Networks
Abstract
Acknowledgments
11.1 Introduction
11.2 Background
11.3 Spatial Aspects of Social Networks
11.4 Cloud-Based Big Data Infrastructure
11.5 Spatial Privacy Case Studies
11.6 Conclusions
Chapter 12: Security and Privacy in Big Data
Abstract
12.1 Introduction
12.2 Secure Queries Over Encrypted Big Data
12.3 Other Big Data Security
12.4 Privacy on Correlated Big Data
12.5 Future Directions
12.6 Conclusions
Chapter 13: Location Inferring in Internet of Things and Big Data
Abstract
Acknowledgements
13.1 Introduction
13.2 Device-based Sensing Using Big Data
13.3 Device-free Sensing Using Big Data
13.4 Conclusion
Part IV: Big Data Applications
Chapter 14: A Framework for Mining Thai Public Opinions
Abstract
Acknowledgments
14.1 Introduction
14.2 XDOM
14.3 Implementation
14.4 Validation
14.5 Case Studies
14.6 Summary and Conclusions
Chapter 15: A Case Study in Big Data Analytics: Exploring Twitter Sentiment Analysis and the Weather
Abstract
Acknowledgments
15.1 Background
15.2 Big Data System Components
15.3 Machine-Learning Methodology
15.4 System Implementation
15.5 Key Findings
15.6 Summary and Conclusions
Chapter 16: Dynamic Uncertainty-Based Analytics for Caching Performance Improvements in Mobile Broadband Wireless Networks
Abstract
16.1 Introduction
16.2 Background
16.3 Related Work
16.4 VoD Architecture
16.5 Overview
16.6 Data Generation
16.7 Edge and Core Components
16.8 INCA Caching Algorithm
16.9 QoE Estimation
16.10 Theoretical Framework
16.11 Experiments and Results
16.12 Synthetic Dataset
16.13 Conclusions and Future Directions
Chapter 17: Big Data Analytics on a Smart Grid: Mining PMU Data for Event and Anomaly Detection
Abstract
Acknowledgments
17.1 Introduction
17.2 Smart Grid With PMUs and PDCs
17.3 Improving Traditional Workflow
17.4 Characterizing Normal Operation
17.5 Identifying Unusual Phenomena
17.6 Identifying Known Events
17.7 Related Efforts
17.8 Conclusion and Future Directions
Chapter 18: eScience and Big Data Workflows in Clouds: A Taxonomy and Survey
Abstract
18.1 Introduction
18.2 Background
18.3 Taxonomy and Review of eScience Services in the Cloud
18.4 Resource Provisioning for eScience Workflows in Clouds
18.5 Open Problems
18.6 Summary
Index
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