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

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

Tevfik Kosar
Release Date: January, 2012|Copyright: © 2012 |Pages: 352
DOI: 10.4018/978-1-61520-971-2
ISBN13: 9781615209712|ISBN10: 1615209719|EISBN13: 9781615209729
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Description & Coverage
Description:

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.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Bulk Data Movement
  • Data and Workflow Management
  • Data Staging and Replication
  • Digital Libraries
  • Hierarchical Storage Systems
  • High Speed Data Streaming
  • Metadata and Semantic Web
  • Network-Aware Storage
  • Parallel and Global File Systems
  • Remote Access to Data
  • Virtual Data Systems
  • Visualization of Large Scale Data
Reviews & Statements

...experts on data intensive computing discuss the challenges imposed by data-intensive applications on distributed systems, and present state-of-the-art solutions proposed to overcome these challenges.

– Tevfik Kosar State University of New York at Buffalo (SUNY), USA

With many books on the market already addressing the large spectrum of big data-related topics, Data Intensive Distributed Computing manages to address the underlying research and technology issues from an original and new viewpoint. The topics addressed are highly relevant to researchers working on data-intensive computing or projects related to developing more efficient data-intensive platforms. [...]

This book is a unified reference and introduction to some of the most relevant research approaches. I do miss a more pragmatic and hands-on introduction to the available implementations and usage scenarios, but the fundamental results and background information on many of the inherent data-intensive architectures make it recommended reading for academic researchers and graduate-level students.

– Radu State, Computing Reviews,
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Editor/Author Biographies
Tevfik Kosar is an Associate Professor of Computer Science and Engineering at University at Buffalo (SUNY). He holds a Ph.D. degree in Computer Science from University of Wisconsin-Madison under the guidance of Prof. Miron Livny. Dr. Kosar's main research interests lie in the cross-section of petascale distributed systems, eScience, Grids, Clouds, and collaborative computing with a focus on large-scale data- intensive distributed applications. He is the primary designer and developer of the Stork distributed data scheduling system which has been adopted by many national and international institutions, and the lead investigator of the state-wide PetaShare distributed storage network in Louisiana. He has published more than fifty academic papers in leading journals and conferences. Some of the awards received by Dr. Kosar include NSF CAREER Award (for his work on “data-aware distributed computing”), LSU Rainmaker Award, LSU Flagship Faculty Award, Baton Rouge Business Report’s Top 40 Under 40 Award, 1012 Corridor’s Young Scientist Award, College of Basic Science’s Research Award, and CCT Faculty of the Year Award. Dr. Kosar’s work on data intensive computing has been funded by NSF, DOE, ONR, DoEd, SURA, and Louisiana Board of Regents.
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