Linux Virtualization - Aug 2012 - Extended Deadline: DataCloud 2012 - The Third International Workshop on Data Intensive Computing in the Clouds

*Call for Papers: The Third International Workshop on Data Intensive
Computing in the Clouds (DataCloud 2012)*

November 11, Salt Lake City, UT, USA (
http://www.cse.buffalo.edu/faculty/tkosar/datacloud2012)

Co-Located with Super Computing 2012, November 10-16, Salt Lake City, UT,
USA (http://sc12.supercomputing.org/)

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 *IMPORTANT DATES*

Abstract and Paper Submission: *September 27, 2012* (extended)
Notification of Acceptance: October 15, 2012
Final Paper Due: October 29, 2012
Workshop: November 11, 2012

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*OVERVIEW*

Applications and experiments in all areas of science are becoming
increasingly complex and more demanding in terms of their computational and
data requirements. Some applications generate data volumes reaching
hundreds of terabytes and even petabytes. As scientific applications become
more data intensive, the management of data resources and dataflow between
the storage and compute resources is becoming the main bottleneck.
Analyzing, visualizing, and disseminating these large data sets has become
a major challenge and data intensive computing is now considered as the
''fourth paradigm'' in scientific discovery after theoretical,
experimental, and computational science.

DataCloud 2012 will provide the scientific community a dedicated forum for
discussing new research, development, and deployment efforts in running
data-intensive computing workloads on Cloud Computing infrastructures. The
DataCloud 2012 workshop will focus on the use of cloud-based technologies
to meet the new data intensive scientific challenges that are not well
served by the current supercomputers, grids or compute-intensive clouds. We
believe the workshop will be an excellent place to help the community
define the current state, determine future goals, and present architectures
and services for future clouds supporting data intensive computing.

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*WORKSHOP SCOPE*

Topics of interest include, but are not limited to:

   - Data-intensive cloud computing applications, characteristics,
   challenges
   - Case studies of data intensive computing in the clouds
   - Performance evaluation of data clouds, data grids, and data centers
   - Energy-efficient data cloud design and management
   - Data placement, scheduling, and interoperability in the clouds
   - Accountability, QoS, and SLAs
   - Data privacy and protection in a public cloud environment
   - Distributed file systems for clouds
   - Data streaming and parallelization
   - New programming models for data-intensive cloud computing
   - Scalability issues in clouds
   - Social computing and massively social gaming
   - 3D Internet and implications
   - Future research challenges in data-intensive cloud computing

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*ORGANIZERS*

   - Tevfik Kosar, University at Buffalo
   - Ioan Raicu, Illinois Institute of Technology & Argonne National
   Laboratory, USA
   - Roger Barga, Microsoft Research

*STEERING COMMITTEE*

   - Ian Foster, University of Chicago & Argonne National Laboratory, USA
   - Geoffrey Fox, Indiana University
   - James Hamilton, Amazon Web Services
   - Manish Parashar, Rutgers University & National Science Foundation
   - Dan Reed, Microsoft Research
   - Rich Wolski, University of California, Santa Barbara

*PROGRAMME COMMITTEE*

   - Samer Al-Kiswany, University of British Columbia, Canada
   - Abhishek Chandra, University of Minnesota
   - Rong N. ChangI, BM Research
   - Kyle Chard, University of Chicago & Argonne National Laboratory
   - Terence Critchlow, Pacific Northwest National Laboratory
   - Murat Demirbas, University at Buffalo
   - Jaliya Ekanayake, Microsoft Research
   - Geoffrey Fox, Indiana University
   - Dennis Gannon, Microsoft Research
   - Rob Gillen, Oak Ridge National Laboratory
   - Maria Indrawan, Monash University, Australia
   - Hui Jin, Oracle
   - Dan Katz, National Science Foundation
   - Steven Ko, University at Buffalo
   - Reagan Moore, University of North Carolina
   - Judy Qui, Indiana University
   - Lavanya Ramakrishnan, Lawrence Berkeley National Laboratory
   - Kui Ren, University at Buffalo
   - Yogesh Simmhan, University of Southern California, USA
   - Borjo Sotomayor, University of Chicago
   - Wei Tang, Argonne National Laboratory
   - Bernard Traversat, Oracle
   - Zhifeng Yun, Louisiana State University
   - Ziming Zheng, Illinois Institute of Technology
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