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Table of Contents
1 COVER
4 PREFACE
6 ACRONYMS
7 CHAPTER 1: Introduction 1.1 Motivation 1.2 Assumptions 1.3 For Whom Is This Book? 1.4 Book Structure
8 CHAPTER 2: Evolution of IT Architectures and Paradigms 2.1 Evolution of IT Architectures 2.2 Actors and Agents 2.3 From ACID to BASE, CAP, and NoSQL – The Database (R)evolution 2.4 The Cloud 2.5 From Distributed Sensor Networks to the Internet of Things and Cyber-Physical Systems 2.6 The Rise of Big Data
9 CHAPTER 3: Sources of Data 3.1 The Internet 3.2 Scientific Data 3.3 Industrial Data 3.4 Internet of Things
10 CHAPTER 4: Big Data Tasks 4.1 Recommender Systems 4.2 Search 4.3 Ad-tech and RTB Algorithms 4.4 Cross-Device Graph Generation 4.5 Forecasting and Prediction Systems 4.6 Social Media Big Data 4.7 Anomaly and Fraud Detection 4.8 New Drug Discovery 4.9 Smart Grid Control and Monitoring 4.10 IoT and Big Data Applications
11 CHAPTER 5: Cloud Computing 5.1 Cloud Enabled Architectures 5.2 Agents and the Cloud
12 CHAPTER 6: Big Data Architectures 6.1 Big Data Computation Models 6.2 Publish-Subscribe Systems 6.3 Stream Processing 6.4 Higer Level Big Data Architectures 6.5 Industry and Other Approaches 6.6 Actor and Agent-Based Big Data Architectures
13 CHAPTER 7: Big Data Analytics, Mining, and Machine Learning 7.1 To SQL or Not to SQL 7.2 Big Data Mining and Machine Learning
14 CHAPTER 8: Physically Distributed Systems – Mobile Cloud, Internet of Things, Edge Computing 8.1 Mobile Cloud 8.2 Edge and Fog Computing 8.3 Internet of Things
16 BIBLIOGRAPHY
17 INDEX
List of Tables
1 Chapter 3Table 3.1 Social media users.Table 3.2 The amount of data collected by 1 million metering devices in a yea...
2 Chapter 5Table 5.1 Cloud computing versus multi-agent systems
3 Chapter 6Table 6.1 Spark versus Flink versus Storm
List of Illustrations
1 Chapter 2Figure 2.1 BI in monolith architecture.Figure 2.2 Data warehouse architecture.Figure 2.3 Akka actor hierarchy.Figure 2.4 BDI architecture.Figure 2.5 Vertical layered architecture.Figure
