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This seems relevant to the Swift community!<br>
Ioan<br>
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<td>[DistComp] CFP: 2nd IEEE International Workshop on
Workflow Models, Systems, Services and Applications in the
Cloud (CloudFlow) 2013</td>
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<th align="RIGHT" nowrap="nowrap" valign="BASELINE">Date: </th>
<td>Mon, 19 Nov 2012 09:22:18 +0800</td>
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<th align="RIGHT" nowrap="nowrap" valign="BASELINE">From: </th>
<td>yong zhao <a class="moz-txt-link-rfc2396E" href="mailto:yongzh04@gmail.com"><yongzh04@gmail.com></a></td>
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<th align="RIGHT" nowrap="nowrap" valign="BASELINE">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:distributed-computing-announce@datasys.cs.iit.edu">distributed-computing-announce@datasys.cs.iit.edu</a></td>
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<div class="gmail_quote">
<div><strong>Second IEEE International Workshop on Workflow
Models, Systems, Services and Applications in the Cloud
(CloudFlow) 2013</strong></div>
<div> </div>
<div><em>To be held in conjunction with the 27th IEEE
International Parallel & Distributed Processing
Symposium (IPDPS) 2013, Cambridge, Boston, Massachusetts,
USA, May 20-24, 2013.</em></div>
<div> </div>
<div><a moz-do-not-send="true"
href="http://www.cloud-uestc.cn/cloudflow/home.html"
target="_blank">http://www.cloud-uestc.cn/cloudflow/home.html</a>
</div>
<div> </div>
<div><strong>Overview</strong></div>
<div> </div>
<div>Cloud computing is gaining tremendous momentum in both
academia and industry, more and more people are migrating
their data and applications into the Cloud. We have observed
wide adoption of the MapReduce computing model and the open
source Hadoop system for large scale distributed data
processing, and a variety of ad hoc mashup techniques that
weave together Web applications. However, these are just first
steps towards managing complex task and data dependencies in
the Cloud, as there are more challenging issues such as large
parameter space exploration, data partitioning and
distribution, scheduling and optimization, smart reruns, and
provenance tracking associated with workflow execution. </div>
<div> </div>
<div>Cloud needs structured and mature workflow technologies to
handle such issues, and vice versa, as Cloud offers
unprecedented scalability to workflow systems, and could
potentially change the way we perceive and conduct research
and experiments. The scale and complexity of the science and
data analytics problems that can be handled can be greatly
increased on the Cloud, and the on-demand nature of resource
allocation on the Cloud will also help improve resource
utilization and user experience.</div>
<div>As Cloud computing provides a paradigm-shifting
utility-oriented computing model in terms of the unprecedented
size of datacenter-level resource pool and the on-demand
resource provisioning mechanism, there are lots of challenges
in bringing Cloud and workflows together. We need high level
languages and computing models for large scale workflow
specification; we need to adapt existing workflow
architectures into the Cloud, and integrate workflow systems
with Cloud infrastructure and resources; we also need to
leverage Cloud data storage technologies to efficiently
distribute data over a large number of nodes and explore data
locality during computation etc. We organize the CloudFlow
workshop as a venue for the workflow and Cloud communities to
define models and paradigms, present their state-of-the-art
work, share their thoughts and experiences, and explore new
directions in realizing workflows in the Cloud.</div>
<div> </div>
<div><strong>Topics:</strong></div>
<div> </div>
<div>We welcome the submission of original work related to the
topics listed below, which include (in the context of Cloud):</div>
<div>• Models and Languages for Large Scale Workflow
Specification</div>
<div>• Workflow Architecture and Framework</div>
<div>• Large Scale Workflow Systems</div>
<div>• Service Workflow</div>
<div>• Workflow Composition and Orchestration</div>
<div>• Workflow Migration into the Cloud</div>
<div>
• Workflow Scheduling and Optimization</div>
<div>• Cloud Middleware in Support of Workflow</div>
<div>• Virtualized Environment</div>
<div>• Workflow Applications and Case Studies </div>
<div>• Performance and Scalability Analysis</div>
<div>• Peta-Scale Data Processing</div>
<div>• Event Processing and Messaging</div>
<div>• Real-Time Analytics</div>
<div>• Provenance</div>
<div> </div>
<div><strong>Paper Submission</strong></div>
<div> </div>
<div>Authors are invited to submit papers with unpublished,
original work. The papers should not exceed 10 single-spaced
double-column pages using 10-point size font on 8.5x11 inch
pages (IEEE conference style), including figures, tables, and
references. </div>
<div> </div>
<div>Paper submission should be done via the online CMT system,
Microsoft’s Academic Conference Management Service (<strong><a
moz-do-not-send="true"
href="https://cmt.research.microsoft.com/CF2013"
target="_blank">https://cmt.research.microsoft.com/CF2013</a></strong>)
by midnight January 9th, 2013 Pacific Time. The final format
should be in PDF. Proceedings of the workshop will be
published by the IEEE Digital Library (indexed by EI) and
distributed at the conference. Selected excellent work may be
eligible for additional post-conference publication as journal
articles or book chapters. Submission implies the willingness
of at least one of the authors to register and present the
paper. </div>
<div> </div>
<div><strong>Important Dates</strong></div>
<div><strong></strong> </div>
<div>Paper submission: January 9th, 2013 </div>
<div>Acceptance notification: February 8th, 2013</div>
<div>Final paper due: Feb 19th, 2013</div>
<div> </div>
<div><strong>Organization</strong></div>
<div> </div>
<div>Workshop Chairs:</div>
<div>Dr. Yong Zhao </div>
<div>University of Electronic Science and Technology of China,
China </div>
<div><a moz-do-not-send="true" href="mailto:yongzh04@gmail.com"
target="_blank">yongzh04@gmail.com</a></div>
<div> </div>
<div>Dr. Cui Lin</div>
<div>California State University, Fresno, USA</div>
<div><a moz-do-not-send="true" href="mailto:clin@csufresno.edu"
target="_blank">clin@csufresno.edu</a></div>
<div> </div>
<div>Dr. Shiyong Lu</div>
<div>Wayne State University, USA</div>
<div><a moz-do-not-send="true" href="mailto:shiyong@wayne.edu"
target="_blank">shiyong@wayne.edu</a></div>
<div> </div>
<div>Program Chair:</div>
<div>Dr. Wenhong Tian </div>
<div>University of Electronic Science and Technology of China,
China </div>
<div> </div>
<div>
Publicity Chair:</div>
<div>Dr. Ruini Xue</div>
<div>University of Electronic Science and Technology of China,
China</div>
<div> </div>
<div><strong>Steering Committee </strong></div>
<div> </div>
<div>• Daniel S. Katz, University of Chicago, U.S.A.</div>
<div>• Mike Wilde, University of Chicago, U.S.A.</div>
<div>• Ewa Deelman, University of South California, U.S.A.</div>
<div>• Tevfik Kosar, University at Buffalo, U.S.A.</div>
<div>• Ilkay Altintas, San Diego Supercomputer Center, U.S.A. </div>
<div>• Ioan Raicu, Illinois Institute of Technology, U.S.A. </div>
<div>• Yogesh Simmhan, University of Southern California, U.S.A.
</div>
<div>• Ian Taylor, Cardiff University, U.K.</div>
<div>• Weimin Zheng, Tsinghua University, China</div>
<div>• Hai Jin, Huazhong University of Science and Engineering,
China</div>
<div>• Wanchun Dou, Nanjing University, China</div>
<div>• Hui Zhang, National Science and Technology
Infrastructure, China</div>
<div> </div>
<div>
<strong>Program Committee </strong></div>
<div> </div>
<div>• Shawn Bowers, Gonzaga University, U.S.A. </div>
<div>• Douglas Thain, University of Notre Dame, U.S.A.</div>
<div>• Ian Gorton, Pacific Northwest National Laboratory, U.S.A.
</div>
<div>• Artem Chebotko, University of Texas at Pan American,
U.S.A. </div>
<div>• Weisong Shi, Wayne State University, U.S.A.</div>
<div>• Paolo Missier, Newcastle University, U.K. </div>
<div>• Wei Tan, IBM T. J. Watson Research Center, U.S.A. </div>
<div>• Jianwu Wang, San Diego Super Computer Center, U.S.A. </div>
<div>• Ping Yang, Binghamton University, U.S.A. </div>
<div>• Jian Guo, Harvard University, U.S.A.</div>
<div>• Liqiang Wang, University of Wyoming, U.S.A. </div>
<div>• Paul Groth, VU University Amsterdam, the Netherlands </div>
<div>• Zhiming Zhao, University of Amsterdam, the Netherlands </div>
<div>• Marta Mattoso, Federal University of Rio de Janeiro,
Brazil </div>
<div>• Wenhong Tian, University of Electronic Science and
Technology of China, China </div>
<div>• Ruini Xue, Tsinghua University, China</div>
<div>• Jian Cao, Shanghai Jiaotong University, China</div>
<div>• Jianxun Liu, Hunan University of Science and Technology,
China</div>
<div>• Song Zhang, Chinese Academy of Sciences, China</div>
<div>• Hua Hu, Hangzhou Dianzi University, China</div>
<div> </div>
<div>==========================================================</div>
<span class="HOEnZb"><font color="#888888">
<div>Yong Zhao</div>
<div><a moz-do-not-send="true"
href="mailto:yongzh04@gmail.com" target="_blank">yongzh04@gmail.com</a></div>
<div>Director, Extreme Scale Network Computing and Service
Laboratory</div>
<div>Professor, School of Computer Science and Engineering</div>
<div>University of Electronic Science and Technology of
China</div>
<div><a moz-do-not-send="true" href="http://cloud-uestc.cn"
target="_blank">http://cloud-uestc.cn</a></div>
<div>==========================================================</div>
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