Networking for Big Data
- Length: 432 pages
- Edition: 1
- Language: English
- Publisher: Chapman and Hall/CRC
- Publication Date: 2015-08-03
- ISBN-10: 1482263491
- ISBN-13: 9781482263497
- Sales Rank: #5455001 (See Top 100 Books)
Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications.
The book is divided into four sections: introduction to Big Data, networking theory and design for Big Data, networking security for Big Data, and platforms and systems for Big Data applications. Focusing on key networking issues in Big Data, the book explains network design and implementation for Big Data. It examines how network topology impacts data collection and explores Big Data storage and resource management.
- Addresses the virtual machine placement problem
- Describes widespread network and information security technologies for Big Data
- Explores network configuration and flow scheduling for Big Data applications
- Presents a systematic set of techniques that optimize throughput and improve bandwidth for efficient Big Data transfer on the Internet
- Tackles the trade-off problem between energy efficiency and service resiliency
The book covers distributed Big Data storage and retrieval as well as security, trust, and privacy protection for Big Data collection, storage, and search. It discusses the use of cloud infrastructures and highlights its benefits to overcome the identified issues and to provide new approaches for managing huge volumes of heterogeneous data.
The text concludes by proposing an innovative user data profile-aware policy-based network management framework that can help you exploit and differentiate user data profiles to achieve better power efficiency and optimized resource management.
Table of Contents
Section I Introduction of Big Data
chapter 1 Orchestrating Science DMZs for Big Data Acceleration: Challenges and Approaches
chapter 2 A Survey of Virtual Machine Placement in Cloud Computing for Big Data
chapter 3 Big Data Management Challenges, Approaches, Tools, and Their Limitations
chapter 4 Big Data Distributed Systems Management
Section II Networking Theory and Design for Big Data
chapter 5 Moving Big Data to the Cloud: Online Cost-Minimizing Algorithms
chapter 6 Data Process and Analysis Technologies of Big Data
chapter 7 Network Configuration and Flow Scheduling for Big Data Applications
chapter 8 Speedup of Big Data Transfer on the Internet
chapter 9 Energy-Aware Survivable Routing in Ever-Escalating Data Environments
Section III Networking Security for Big Data
chapter 10 A Review of Network Intrusion Detection in the Big Data Era: Challenges and Future Trends
chapter 11 Toward MapReduce-Based Machine-Learning Techniques for Processing Massive Network Threat Monitoring
chapter 12 Anonymous Communication for Big Data
chapter 13 Flow-Based Anomaly Detection in Big Data
Section IV Platforms and Systems for Big Data Applications
chapter 14 Mining Social Media with SDN-Enabled Big Data Platform to Transform TV Watching Experience
chapter 15 Trends in Cloud Infrastructures for Big Data
chapter 16 A User Data Profile-Aware Policy-Based Network Management Framework in the Era of Big Data
chapter 17 Circuit Emulation for Big Data Transfers in Clouds