Data Intensive Computing Applications for Big Data

Data Intensive Computing Applications for Big Data PDF Author: M. Mittal
Publisher: IOS Press
ISBN: 1614998140
Category : Computers
Languages : en
Pages : 618

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Book Description
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 brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.

Data Intensive Computing Applications for Big Data

Data Intensive Computing Applications for Big Data PDF Author: M. Mittal
Publisher: IOS Press
ISBN: 1614998140
Category : Computers
Languages : en
Pages : 618

Get Book Here

Book Description
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 brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.

Big Data Analytics for Sensor-Network Collected Intelligence

Big Data Analytics for Sensor-Network Collected Intelligence PDF Author: Hui-Huang Hsu
Publisher: Morgan Kaufmann
ISBN: 012809625X
Category : Computers
Languages : en
Pages : 328

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Book Description
Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services. It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality. In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS - Contains contributions from noted scholars in computer science and electrical engineering from around the globe - Provides a broad overview of recent developments in sensor collected intelligence - Edited by a team comprised of leading thinkers in big data analytics

Designing Data-Intensive Applications

Designing Data-Intensive Applications PDF Author: Martin Kleppmann
Publisher: "O'Reilly Media, Inc."
ISBN: 1491903104
Category : Computers
Languages : en
Pages : 658

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Book Description
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

Cloud Computing

Cloud Computing PDF Author: Frederic Magoules
Publisher: CRC Press
ISBN: 1466507837
Category : Computers
Languages : en
Pages : 230

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Book Description
As more and more data is generated at a faster-than-ever rate, processing large volumes of data is becoming a challenge for data analysis software. Addressing performance issues, Cloud Computing: Data-Intensive Computing and Scheduling explores the evolution of classical techniques and describes completely new methods and innovative algorithms. The

Cloud Computing for Data-Intensive Applications

Cloud Computing for Data-Intensive Applications PDF Author: Xiaolin Li
Publisher: Springer
ISBN: 1493919059
Category : Computers
Languages : en
Pages : 425

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Book Description
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.

Data-Intensive Computing

Data-Intensive Computing PDF Author: Ian Gorton
Publisher: Cambridge University Press
ISBN: 1139788507
Category : Computers
Languages : en
Pages : 299

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Book Description
The world is awash with digital data from social networks, blogs, business, science and engineering. Data-intensive computing facilitates understanding of complex problems that must process massive amounts of data. Through the development of new classes of software, algorithms and hardware, data-intensive applications can provide timely and meaningful analytical results in response to exponentially growing data complexity and associated analysis requirements. This emerging area brings many challenges that are different from traditional high-performance computing. This reference for computing professionals and researchers describes the dimensions of the field, the key challenges, the state of the art and the characteristics of likely approaches that future data-intensive problems will require. Chapters cover general principles and methods for designing such systems and for managing and analyzing the big data sets of today that live in the cloud and describe example applications in bioinformatics and cybersecurity that illustrate these principles in practice.

Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management

Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management PDF Author: Kosar, Tevfik
Publisher: IGI Global
ISBN: 1615209727
Category : Computers
Languages : en
Pages : 353

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Book Description
"This book focuses on the challenges of distributed systems imposed by the data intensive applications, and on the different state-of-the-art solutions proposed to overcome these challenges"--Provided by publisher.

Handbook of Data Intensive Computing

Handbook of Data Intensive Computing PDF Author: Borko Furht
Publisher: Springer Science & Business Media
ISBN: 1461414156
Category : Computers
Languages : en
Pages : 795

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Book Description
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.

Cloud Computing and Big Data

Cloud Computing and Big Data PDF Author: C. Catlett
Publisher: IOS Press
ISBN: 161499322X
Category : Computers
Languages : en
Pages : 260

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Book Description
Cloud computing offers many advantages to researchers and engineers who need access to high performance computing facilities for solving particular compute-intensive and/or large-scale problems, but whose overall high performance computing (HPC) needs do not justify the acquisition and operation of dedicated HPC facilities. There are, however, a number of fundamental problems which must be addressed, such as the limitations imposed by accessibility, security and communication speed, before these advantages can be exploited to the full. This book presents 14 contributions selected from the International Research Workshop on Advanced High Performance Computing Systems, held in Cetraro, Italy, in June 2012. The papers are arranged in three chapters. Chapter 1 includes five papers on cloud infrastructures, while Chapter 2 discusses cloud applications. The third chapter in the book deals with big data, which is nothing new – large scientific organizations have been collecting large amounts of data for decades – but what is new is that the focus has now broadened to include sectors such as business analytics, financial analyses, Internet service providers, oil and gas, medicine, automotive and a host of others. This book will be of interest to all those whose work involves them with aspects of cloud computing and big data applications.

Web-Scale Data Management for the Cloud

Web-Scale Data Management for the Cloud PDF Author: Wolfgang Lehner
Publisher: Springer Science & Business Media
ISBN: 1461468566
Category : Computers
Languages : en
Pages : 209

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Book Description
The efficient management of a consistent and integrated database is a central task in modern IT and highly relevant for science and industry. Hardly any critical enterprise solution comes without any functionality for managing data in its different forms. Web-Scale Data Management for the Cloud addresses fundamental challenges posed by the need and desire to provide database functionality in the context of the Database as a Service (DBaaS) paradigm for database outsourcing. This book also discusses the motivation of the new paradigm of cloud computing, and its impact to data outsourcing and service-oriented computing in data-intensive applications. Techniques with respect to the support in the current cloud environments, major challenges, and future trends are covered in the last section of this book. A survey addressing the techniques and special requirements for building database services are provided in this book as well.