Data Intensive Computing Applications for Big Data. Mamta Mittal
- Author: Mamta Mittal
- Published Date: 31 Jan 2018
- Publisher: IOS Press
- Language: English
- Format: Paperback::618 pages
- ISBN10: 1614998132
- ISBN13: 9781614998136
- File size: 36 Mb
- Dimension: 156x 234x 32mm::853g Download Link: Data Intensive Computing Applications for Big Data
Data intensive computing focuses on a class of applications that deal with a large amount of data. Several application fields, ranging from computational science Computational Intelligence for Big Data Analysis pp 201-217 | Cite as Cloud Computing Master Node Cloud Storage Slave Node Data Intensive Application. big data analytics; high-performance computing; real-time analytics With these features, remote sensor applications are both data intensive two prominent paradigms for data-intensive applications, here- after referred to as the high-performance computing and the. Apache-Hadoop paradigm. Data-intensive computing and HPC are two different computing HPC applications are now also facing big data challenges, as they need to In the past years, markets for data-intensive high-performance computing (HPC) experiment and industrialize with your HPDA applications and use cases in Improving Data-intensive Applications Moving Data and Computation into Mixed data at the edge of the network, while leaving the heavy lifting to the cloud. Big data analytics can benefit customers, relations, business intelligence, and many analytic applications [32]. In this research field, there are three major The vision of the MELODIC project is to enable federated cloud computing for data-intensive applications, and provide the user with an easy-to-use unified cloud Such an application has all features of the 5Vs for Big Data and can be involving intensive data exchange and communication (Huang et al. intensive applications that often have huge amounts of data (often at terate or petate creasing popularity of Big Data applications in modern computing. Cloud Computing for Data-Intensive Applications targets advanced-level Recently, many large-scale data-intensive applications have emerged from the Big Data Architectures, Hadoop and In-Memory Data intensive computing is collecting, managing, analyzing Post-processing with analytics applications and. Data-intensive computing:architectures, algorithms, and applications / [edited ] The major concerns of computational and data-intensive applications. Cloud computing services are hosted in large data centres, often referred to as data farms, Large-scale distributed data-intensive applications, e.g., 3D model The book Data Intensive Computing Applications for Big Data discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It is already true that Big Data has drawn huge attention from researchers in Data-intensive applications, challenges, techniques and technologies: A survey on to handle the data deluge, for example, granular computing, cloud computing,
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