Cloud Computing For Data Intensive Applications
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Cloud Computing for Data-Intensive Applications
This book presents a range of cloud computing platforms for data-intensive scientific applications. It covers systems that deliver infrastructure as a service, including: HPC as a service; virtual networks as a service; scalable and reliable storage; algorithms that manage vast cloud resources and applications runtime; and programming models that enable pragmatic programming and implementation toolkits for eScience applications. Many scientific applications in clouds are also introduced, such as bioinformatics, biology, weather forecasting and social networks. Most chapters include case studies. Cloud Computing for Data-Intensive Applications targets advanced-level students and researchers studying computer science and electrical engineering. Professionals working in cloud computing, networks, databases and more will also find this book useful as a reference.
Handbook of Data Intensive Computing
Author: Borko Furht
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-12-10
Data Intensive Computing refers to capturing, managing, analyzing, and understanding data at volumes and rates that push the frontiers of current technologies. The challenge of data intensive computing is to provide the hardware architectures and related software systems and techniques which are capable of transforming ultra-large data into valuable knowledge. Handbook of Data Intensive Computing is written by leading international experts in the field. Experts from academia, research laboratories and private industry address both theory and application. Data intensive computing demands a fundamentally different set of principles than mainstream computing. Data-intensive applications typically are well suited for large-scale parallelism over the data and also require an extremely high degree of fault-tolerance, reliability, and availability. Real-world examples are provided throughout the book. Handbook of Data Intensive Computing is designed as a reference for practitioners and researchers, including programmers, computer and system infrastructure designers, and developers. This book can also be beneficial for business managers, entrepreneurs, and investors.
Building Scalable Data-Intensive Applications
Building Scalable Data-Intensive Applications explores the vast landscape of digital data from social networks, blogs, business, science, and engineering. This book delves into data-intensive computing, which is essential for understanding and processing massive amounts of data. Utilizing the latest software, algorithms, and hardware, data-intensive applications deliver timely and meaningful insights, addressing the challenges posed by exponentially growing data complexity. We provide a comprehensive reference for computing professionals and researchers, covering the field's scope, key challenges, and state-of-the-art approaches required for future data-intensive problems. Our chapters include general principles and methods for designing and managing systems that analyze vast datasets, particularly those stored in the cloud. Additionally, we explore practical applications in cybersecurity and bioinformatics to illustrate these principles in action. Building Scalable Data-Intensive Applications is an invaluable resource for anyone looking to navigate and harness the power of data-intensive computing.