Resource Management For Big Data Platforms
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| Author | : Florin Pop |
| Publisher | : Springer |
| Total Pages | : 509 |
| Release | : 2016-10-27 |
| Genre | : Computers |
| ISBN | : 3319448811 |
Serving as a flagship driver towards advance research in the area of Big Data platforms and applications, this book provides a platform for the dissemination of advanced topics of theory, research efforts and analysis, and implementation oriented on methods, techniques and performance evaluation. In 23 chapters, several important formulations of the architecture design, optimization techniques, advanced analytics methods, biological, medical and social media applications are presented. These chapters discuss the research of members from the ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). This volume is ideal as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary works in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers to grasp the key concerns and their potential solutions.
| Author | : Florin Pop |
| Publisher | : Springer Nature |
| Total Pages | : 300 |
| Release | : 2021-09-28 |
| Genre | : Computers |
| ISBN | : 3030388360 |
This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge. The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are needed for real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.
| Author | : Yusuf Aytas |
| Publisher | : John Wiley & Sons |
| Total Pages | : 336 |
| Release | : 2021-07-08 |
| Genre | : Mathematics |
| ISBN | : 1119690951 |
DESIGNING BIG DATA PLATFORMS Provides expert guidance and valuable insights on getting the most out of Big Data systems An array of tools are currently available for managing and processing data—some are ready-to-go solutions that can be immediately deployed, while others require complex and time-intensive setups. With such a vast range of options, choosing the right tool to build a solution can be complicated, as can determining which tools work well with each other. Designing Big Data Platforms provides clear and authoritative guidance on the critical decisions necessary for successfully deploying, operating, and maintaining Big Data systems. This highly practical guide helps readers understand how to process large amounts of data with well-known Linux tools and database solutions, use effective techniques to collect and manage data from multiple sources, transform data into meaningful business insights, and much more. Author Yusuf Aytas, a software engineer with a vast amount of big data experience, discusses the design of the ideal Big Data platform: one that meets the needs of data analysts, data engineers, data scientists, software engineers, and a spectrum of other stakeholders across an organization. Detailed yet accessible chapters cover key topics such as stream data processing, data analytics, data science, data discovery, and data security. This real-world manual for Big Data technologies: Provides up-to-date coverage of the tools currently used in Big Data processing and management Offers step-by-step guidance on building a data pipeline, from basic scripting to distributed systems Highlights and explains how data is processed at scale Includes an introduction to the foundation of a modern data platform Designing Big Data Platforms: How to Use, Deploy, and Maintain Big Data Systems is a must-have for all professionals working with Big Data, as well researchers and students in computer science and related fields.
| Author | : Jan Kunigk |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 688 |
| Release | : 2018-12-05 |
| Genre | : Computers |
| ISBN | : 1491969229 |
There’s a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you’ll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform. Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You’ll explore the vast landscape of tools available in the Hadoop and big data realm in a thorough technical primer before diving into: Infrastructure: Look at all component layers in a modern data platform, from the server to the data center, to establish a solid foundation for data in your enterprise Platform: Understand aspects of deployment, operation, security, high availability, and disaster recovery, along with everything you need to know to integrate your platform with the rest of your enterprise IT Taking Hadoop to the cloud: Learn the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability
| Author | : Joanna Kołodziej |
| Publisher | : Springer |
| Total Pages | : 171 |
| Release | : 2018-01-30 |
| Genre | : Technology & Engineering |
| ISBN | : 3319737678 |
This book consists of eight chapters, five of which provide a summary of the tutorials and workshops organised as part of the cHiPSet Summer School: High-Performance Modelling and Simulation for Big Data Applications Cost Action on “New Trends in Modelling and Simulation in HPC Systems,” which was held in Bucharest (Romania) on September 21–23, 2016. As such it offers a solid foundation for the development of new-generation data-intensive intelligent systems. Modelling and simulation (MS) in the big data era is widely considered the essential tool in science and engineering to substantiate the prediction and analysis of complex systems and natural phenomena. MS offers suitable abstractions to manage the complexity of analysing big data in various scientific and engineering domains. Unfortunately, big data problems are not always easily amenable to efficient MS over HPC (high performance computing). Further, MS communities may lack the detailed expertise required to exploit the full potential of HPC solutions, and HPC architects may not be fully aware of specific MS requirements. The main goal of the Summer School was to improve the participants’ practical skills and knowledge of the novel HPC-driven models and technologies for big data applications. The trainers, who are also the authors of this book, explained how to design, construct, and utilise the complex MS tools that capture many of the HPC modelling needs, from scalability to fault tolerance and beyond. In the final three chapters, the book presents the first outcomes of the school: new ideas and novel results of the research on security aspects in clouds, first prototypes of the complex virtual models of data in big data streams and a data-intensive computing framework for opportunistic networks. It is a valuable reference resource for those wanting to start working in HPC and big data systems, as well as for advanced researchers and practitioners.
| Author | : David Loshin |
| Publisher | : Elsevier |
| Total Pages | : 143 |
| Release | : 2013-08-23 |
| Genre | : Computers |
| ISBN | : 0124186645 |
Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. - Guides the reader in assessing the opportunities and value proposition - Overview of big data hardware and software architectures - Presents a variety of technologies and how they fit into the big data ecosystem
| Author | : Kuan-Ching Li |
| Publisher | : CRC Press |
| Total Pages | : 478 |
| Release | : 2015-02-23 |
| Genre | : Computers |
| ISBN | : 1482240564 |
As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages.Pre
| Author | : José María Cavanillas |
| Publisher | : Springer |
| Total Pages | : 312 |
| Release | : 2016-04-04 |
| Genre | : Computers |
| ISBN | : 3319215698 |
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.
| Author | : Constandinos X. Mavromoustakis |
| Publisher | : Springer |
| Total Pages | : 381 |
| Release | : 2016-11-19 |
| Genre | : Technology & Engineering |
| ISBN | : 3319451456 |
This book reports on the latest advances on the theories, practices, standards and strategies that are related to the modern technology paradigms, the Mobile Cloud computing (MCC) and Big Data, as the pillars and their association with the emerging 5G mobile networks. The book includes 15 rigorously refereed chapters written by leading international researchers, providing the readers with technical and scientific information about various aspects of Big Data and Mobile Cloud Computing, from basic concepts to advanced findings, reporting the state-of-the-art on Big Data management. It demonstrates and discusses methods and practices to improve multi-source Big Data manipulation techniques, as well as the integration of resources availability through the 3As (Anywhere, Anything, Anytime) paradigm, using the 5G access technologies.
| Author | : A.J. Tallón-Ballesteros |
| Publisher | : IOS Press |
| Total Pages | : 686 |
| Release | : 2023-02-28 |
| Genre | : Computers |
| ISBN | : 1643683799 |
The digital era has brought about important changes that continue to affect all our lives. Efficient management and storage of digital information has become crucial, as has the ability to access that information quickly and efficiently, and priorities are to allow for the saving of digital data in many different ways, and to avoid the loss of information in the event of a malfunction. This book presents the 65 papers presented at DMI2022, the first in the new annual conference series Digitalization and Management Innovation (DMI), held as a hybrid event in Beijing, China, on 26 November 2022. A total of 190 submissions were received for the conference, and the papers presented here were selected after careful and conscientious review, bearing in mind the breadth and depth of the research topics falling within the scope of digital and management innovation and resulting in an acceptance rate of 34%. Topics covered include digital transformation, supply chains, business models, and block chain, enterprises, banking, and sustainability, as well as policy in artificial intelligence, the gig economy, the post-epidemic era, green supply, citizenship behavior, human resource management, human relationships, agriculture, and environmental matters. Presenting original ideas and results of general significance and supported by clear reasoning, and compelling evidence and methods, the book will be of interest to all those whose work involves the management of digital data.
