The trend in scientific, as well as commercial, applications from a diverse range of fields has been towards being more and more data-intensive over time. Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management focuses on the challenges of distributed systems imposed by data intensive applications and on the different state-of-the-art solutions proposed to overcome such challenges. Providing hints on how to manage low-level data handling issues when performing data intensive distributed computing, this publication is ideal for scientists, researchers, engineers, and application developers, alike. With the knowledge of the correct data management techniques for their applications, readers will be able to focus on their primary goal, assured that their data management needs are handled reliably and efficiently.
The trend in scientific, as well as commercial, applications from a diverse range of fields has been towards being more and more data-intensive over time. Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management focuses on the challenges of distributed systems imposed by data intensive applications and on the different state-of-the-art solutions proposed to overcome such challenges. Providing hints on how to manage low-level data handling issues when performing data intensive distributed computing, this publication is ideal for scientists, researchers, engineers, and application developers, alike. With the knowledge of the correct data management techniques for their applications, readers will be able to focus on their primary goal, assured that their data management needs are handled reliably and efficiently.
This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems...
This book is focused on the development of a data integration framework for retrieval of biodiversity information from heterogeneous and distributed data sources. The data integration system proposed...
This book presents new approaches that advance research in all aspects of agent-based models, technologies, simulations and implementations for data intensive applications. The nine chapters contain...
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...
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