An Efficient Big Data Analytics Using Grid Framework and ANT Based Algorithm

Abstract

Big Data is about the volume, variety and velocity of information being generated today and the opportunity that results from efficiently leveraging data for insight and competitive advantage. The Big Data describes a new generation of technologies and architectures designed to economically extract value from these very large and diverse volumes of data by enabling high- velocity capture, discovery, and/or analysis. In big data is term important of three main characteristics. The framework for processing Big Data consists of a number of software tools that will be presented in this thesis, and briefly listed. That is the area where using Grid Technologies can provide help. Grid Computing refers to a special kind of istributed computing. The main purpose of this article is to present a way of processing Big Data using Grid Technologies. For that, the framework for managing Big Data will be  resented along with the way to implement it around grid architecture. However, there are many challenges in dealing with big data such as storage, transfer, management and manipulation of big data. Many techniques are required to  xplore the hidden pattern inside the big data which have limitations in terms of hardware and software implementation. In this thesis, the big data has been implemented using grid framework technologies and ANT based algorithm. The performance of the big data and grid framework technology implementation is evaluated using the parameters of the big data analytics and proved that the grid framework is supports effectively for big data process.