[hpc-announce] IEEE DataCloud 2013 -- at SuperComputing/SC'13

Ziming Zheng zimingzheng at uchicago.edu
Mon Jun 3 22:25:49 CDT 2013

Call for Papers

The Fourth International Workshop on
Data Intensive Computing in the Clouds (DataCloud 2013) 2013
November 17th, 2013
Denver, Colorado, USA

Co-located with IEEE/ACM International Conference for
High Performance Computing, Networking, Storage and Analysis (SC13)

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.
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.

As scientific applications become more data intensive, the techology of handling
"Big Data" have gathered great importance. This necessity has made that applications
have seen an increasing adoption on clouds infrastructures. The computing models,system
software, programming models, analysis frameworks, and other clouds sevices
need to evolve and accommodate them to face the challenge of big data applications.

The fourth international workshop on Data-intensive Computing in the Clouds
(DataCloud 2013) 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 2013 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.

* Big data analytics
* 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

Paper Submission and Publication
Authors are invited to submit papers with unpublished, original work of not more than 5 pages of double column text using single spaced 10 point size on 8.5 x 11 inch pages, as per ACM 8.5 x 11 manuscript guidelines; document templates can be found at http://www.acm.org/sigs/publications/proceedings-templates. The final 5 page papers in PDF format must be submitted online at https://cmt.research.microsoft.com/DataCloud2013/ before the deadline of September 1st, 2013 at 11:59PM PST. Papers will be peer-reviewed, and accepted papers will be published in the workshop proceedings as part of the ACM digital library (pending approval). Notifications of the paper decisions will be sent out by October 13th, 2011. Selected excellent work may be eligible for additional post-conference publication as journal articles. Submission implies the willingness of at least one of the authors to register and present the paper. For more information, please see http://datasys.cs.iit.edu/events/DataCloud2013/.

Important Dates
* Paper submission: September 1, 2013
* Acceptance notification: October 13, 2013
* Final papers due: November 10, 2013

Committee Members
Workshop Chairs
* Yong Zhao, University of Electronic Science and Technology of China, China
* Ziming Zheng, University of Chicago, USA
* Hui Jin, Oracle, USA

Steering Committee
* Roger Barga, Microsoft Research, USA
* Ian Foster, University of Chicago & Argonne National Laboratory, USA
* Geoffrey Fox, Indiana University, USA
* James Hamilton, Amazon, USA
* Tevfik Kosar, University at Buffalo, USA

* Manish Parashar, Rutgers University, USA
* Ioan Raicu, Illinois Institute of Technology & Argonne National Laboratory, USA
* Dan Reed, Microsoft Research, USA
* Rich Wolski, University of California at Santa Barbara, USA
* Rong Chang, IBM, USA

Program Committee
* Abhishek Chandra, University of Minnesota, USA
* Alexandru Iosup, Delft University of Technology, USA
* Bernard Traversat, Oracle Corporation, USA
* Borja Sotomayor, University of Chicago, USA
* Cong Du, Arista Network, USA
* Dan Katz, University of Chicago, USA
* Dong Li, Oak Ridge National Laboratory, USA
* Douglas Thain,University of Notre Dame,USA
* Erwin Laure, CERN, Switzerland
* Geoffrey Fox, Indiana University, USA
* Hangwei Qian,VMWare, USA
* Ian Foster, University of Chicago and Argonne National Laboratory, USA
* Jack Lange, University of Pittsburgh, USA
* Jim Myers, Rensselaer Polytechnic Institute, USA
* Judy Qui, Indiana University, USA
* Kyle Chard, University of Chicago, USA
* Lavanya Ramakrishnan, Lawrence Berkeley National Laboratory, USA
* Maria Indrawan, Monash University, Australia
* Matei Ripeanu, University of British Columbia, Canada
* Murat Demirbas, SUNY Buffalo, USA
* Peter Dinda, Northwestern University, USA
* Peter Kacsuk, Hungarian Academy of Sciences, Hungary
* Reagan Moore, University of North Carolina at Chapel Hill, USA
* Rob Ross, Argonne National Labs, USA
* Rob Gillen, Oak Ridge National Laboratory, USA
* Ruini Xue, University of Electronic Science and Technology, China
* Samer Al-Kiswany, University of British Columbia, Canada
* Steven Ko, SUNY Buffalo, USA
* Suraj Pandey, IBM Australia Research Lab, Australia
* Venkat Vishwanath, Argonne National Laboratory, USA
* Teng Ma, Netapp, USA
* Wei Tang, Argonne National Laboratory, USA
* Yogesh Simmhan, University of Southern California, USA
* Zhiang Wu, Nanjing University of Finance and Economics, China
* Zhifeng Yun, Louisiana State University, USA
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