2 :0 0 p m - 6 :0 0 p m
TUTORIAL IX
Data Grid Management Systems: Towards
Knowledge Grid Networks
Arcot Rajasekar and Arun Jagatheesan
San Diego Supercomputer Center
University of California, San Diego
Audience: Since the tutorial covers basics,
open research issues and demonstration
sessions, a wide variety of people fall into the
category of "intended audience". Based on
similar experiences before at NPACI (National
Partnership for Advanced Computing
Infrastructure), the following people would be
benefited: Beginners, Students: The introductory
sections will provide valuable information
on Data Grids, Computational Grids and
projects using these technologies. Researchers:
Investigators who already are in HPC will be
updated on new challenges and methodology
in data management. System Developers:
Information about data grid requirements and
components will showcase future development
challenges. Commercial Companies: The case
studies would provide solutions to similar
problems in the commercial world.
Course Description: Data grids handle large-scale,
distributed, heterogeneous collections of
data shared among virtual organizations. This
tutorial provides insight into opportunities,
components and case studies of data grids and
explores their usage in high performance and
large scale computing environments. Starting
with challenges in data handling, the tutorial
will also provide an overview of the data grid
technology, design philosophy, best practices
and services for the next generation commercial
and scientific applications. It will introduce
the burgeoning field of data grid management
systems (DGMS), and illustrate real-life grids
(GriPhyN, NVO, BIRN, etc.) and grid components
(Storage Resource Broker, Grid Portal,
etc.). If possible, a hands-on session to use and
"feel" a working data grid system will be
provided. The course outline is as follows:
1) Introduction to Data Grids (What?),
2) Requirement for Data Grids (Why?),
3) Data Grid Components (How?), 4) Case
Studies (Where?), 5) SRB Demo/Hands On
(Can I?), 6) Other Technologies (What else?),
7) Data Grid Management Systems,
8) Knowledge Grid Network (What next?),
and 9) Uncharted Waters (New challenges?).
Lecturers: Dr. Arcot Rajasekar is the Director
of the Data Grid Technologies Group at the
San Diego Supercomputer Center at UCSD.
His research interests include data grids, digital
library systems, persistent archives and distributed
data collection & metadata management.
He is a key architect of the SDSC
Storage Resource Broker, an intelligent data
grid integrating distributed data archives, file
repositories and digital collections. Dr. Rajasekar
received his PhD from the University of Maryland
and has more than 50 publications in
artificial intelligence, databases and data grid
systems. His email address is [email protected].
Arun Jagatheesan is a Visiting Scholar at the
San Diego Supercomputer Center and a member
of the High Energy Physics Group at the
University of Florida. His current research
interests include Internet Computing, Data
Grid Management, Semantic Web and
Workflow Systems. He is involved in research
and development of GriPhyN (Grid Physics
Network), SRB Web Services and Data Grid
Management Systems at SDSC. Jagatheesan
received his M.S in Computer Science from
the University of Florida. His email address is
[email protected].
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