Techniques and Environments for Big Data Analysis: Parallel, Cloud, and Grid Computing

This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.

Table of Contents

Chapter 1 Introduction to Big Data Analysis
Chapter 2 Parallel Environments
Chapter 3 A Deep Dive into the Hadoop World to Explore Its Various Performances
Chapter 4 Natural Language Processing and Machine Learning for Big Data
Chapter 5 Big Data and Cyber Foraging: Future Scope and Challenges
Chapter 6 Parallel GA in Big Data Analysis
Chapter 7 Evolutionary Algorithm Based Techniques to Handle Big Data
Chapter 8 Statistical and Evolutionary Feature Selection Techniques Parallelized Using MapReduce Programming Model
Chapter 9 The Role of Grid Technologies: A Next Level Combat with Big Data