Techniques and Environments for Big Data Analysis
Parallel, Cloud, and Grid Computing
Published on 16. February 2016
Book
Hardback
XI, 191 pages
978-3-319-27518-5 (ISBN)
Description
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.
More details
Series
Edition
1st ed. 2016
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Research
Illustrations
27 s/w Abbildungen, 76 farbige Abbildungen
XI, 191 p. 103 illus., 76 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 17 mm
Weight
477 gr
ISBN-13
978-3-319-27518-5 (9783319275185)
DOI
10.1007/978-3-319-27520-8
Schweitzer Classification
Other editions
Additional editions
B. S.P. Mishra | Satchidananda Dehuri | Euiwhan Kim
Techniques and Environments for Big Data Analysis
Parallel, Cloud, and Grid Computing
Book
03/2018
Springer
€106.99
Shipment within 10-15 days
B. S.P. Mishra | Satchidananda Dehuri | Euiwhan Kim
Techniques and Environments for Big Data Analysis
Parallel, Cloud, and Grid Computing
E-Book
02/2016
Springer
€96.29
Available for download
Persons
Content
Introduction to Big Data Analysis.- Parallel Environments.- A Deep Dive into the Hadoop World to Explore its VariousPerformances.- Natural Language Processing and Machine Learning for Big Data.- Big Data and Cyber Foraging: Future Scope and Challenges.- Parallel GA in Big Data Analysis.- Evolutionary Algorithm Based Techniques to Handle Big Data.- Statistical and Evolutionary Feature Selection TechniquesParallelized using MapReduce Programming Model.- A Data Aware Scheme for Scheduling Big-Data Applications on SAVANNA Hadoop.- The Role of Grid Technologies: A Next Level Combat with Big Data.