Big data analytics for sensor-network collected intelligence / edited by Hui-Huang Hsu, Chuan-Yu Chang, Ching-Hsien Hsu.
Material type:
TextSeries: Intelligent data centric systemsPublisher: London, United Kingdom : Academic Press, an imprint of Elsevier, 2017Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9780128096253; 012809625XSubject(s): Big data | Wireless sensor networks | Cloud computing | COMPUTERS -- Cloud Computing | Big data | Cloud computing | Wireless sensor networksGenre/Form: Electronic books.Additional physical formats: Print version:: Big data analytics for sensor-network collected intelligence.DDC classification: 005.7 LOC classification: QA76.9.B45Online resources: ScienceDirect | Item type | Current library | Call number | Status | Date due | Barcode |
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Mysore University Main Library | Not for loan | EBKELV734 |
Front Cover; Big Data Analytics for Sensor-Network Collected Intelligence; Copyright; Contents; List of Contributors; Preface; Acknowledgments; Part I: Big Data Architecture and Platforms; Chapter 1: Big Data: A Classification of Acquisition and Generation Methods; 1. Big Data: A Classification; 1.1. Characteristics of Big Data; 2. Big Data Generation Methods; 2.1. Data Sources; 2.1.1. Born-digital data; 2.1.2. Sensor data; 2.2. Data Types; 2.2.1. Structured data; 2.2.2. Unstructured data; 3. Big Data: Data Acquisition Methods; 3.1. Interface Methods; 3.1.1. Command-line interfaces.
3.1.2. Graphical user interfaces3.1.3. Context-sensitive user interfaces; 3.1.4. Web-based user interfaces; 3.1.5. Adaptive user interfaces or intelligent user interfaces; 3.1.6. Natural user interfaces; 3.1.7. Voice interfaces; 3.1.8. Gesture-based interfaces; 3.1.9. Multitouch gesture interface; 3.1.10. Touchless gesture interfaces; 3.2. Interface Devices; 3.2.1. Keyboard; 3.2.2. Mice; 3.2.3. Joystick; 3.2.4. Stylus; 3.2.5. Touchpad; 3.2.6. Touchscreens; 3.2.7. Kinect; 3.2.8. Leap motion; 3.2.9. Myo; 3.2.10. Wearable devices; 4. Big Data: Data Management.
4.1. Data Representation and Organization4.1.1. File formats; Javascript object notation records (JSON); Binary Javascript object notation records (BSON); Comma-separated values (CSV); Sequence file; Record columnar files; Optimized row columnar files (ORC files); Parquet files; Avro files; 4.1.2. Data compression; 4.1.3. Hadoop codecs; 4.2. Databases; 4.2.1. Dynamic schema; 4.2.2. Sharding, replication and auto-caching; 4.2.3. NoSQL types; Key-value stores; Document stores; Column-oriented stores; Graph stores; 4.3. Data Fusion and Data Integration; 5. Summary; References; Glossary.
Chapter 2: Cloud Computing Infrastructure for Data Intensive Applications1. Introduction; 2. Big Data Nature and Definition; 2.1. Big Data in Science and Industry; 2.2. Big Data and Social Network/Data; 2.3. Big Data Technology Definition: From 6V to 5 Parts; 3. Big Data and Paradigm Change; 3.1. Big Data Ecosystem; 3.2. New Features of the BDI; 3.3. Moving to Data-Centric Models and Technologies; 4. Big Data Architecture Framework and Components; 4.1. Defining the Big Data Architecture Framework; 4.2. Data Management and Big Data Lifecycle; 4.3. Data Structures and Data Models for Big Data.
4.4. NIST Big Data Reference Architecture4.5. General Big Data System Requirements; 4.5.1. Data sources requirements (DSR); 4.5.2. Transformation (applications) provider requirements (TPR); 4.5.3. Capability (framework) provider requirements (CPR); 4.5.4. Data consumer requirements (DCR); 4.5.5. Security and privacy requirements (SPR); 4.5.6. Lifecycle management requirements (LMR); 4.5.7. Other requirements (OR); 5. Big Data Infrastructure; 5.1. BDI Components; 5.2. Big Data Stack Components and Technologies; 5.3. Example of Cloud-Based Infrastructure for Distributed Data Processing.
Includes index.
Online resource; title from PDF title page (ScienceDirect, viewed February. 17, 2017).
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