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[HTCondor-users] Call for Papers: IEEE Transactions on Cloud Computing - Special Issue on Scientific Cloud Computing (deadline Jul 31, 2014)

Dear colleagues,
Please consider the following CFP for your contributions.
Call for Papers

IEEE Transactions on Cloud Computing 
Special Issue on Scientific Cloud Computing 


Paper Submissions Due: July 31, 2014
First Round Decision: September 30,2014
Major Revisions Due (if necessary): October 31, 2014
Final Decision: December 1, 2014
Journal Publication: TBD


Computational and Data-Driven Sciences have become the third and fourth pillar 
of scientific discovery in addition to experimental and theoretical sciences. 
Scientific Computing has already begun to change how science is done, enabling 
scientific breakthroughs through new kinds of experiments that would have been 
impossible only a decade ago. It is the key to solving “grand challenges” in 
many domains and providing breakthroughs in new knowledge, and it comes in many 
shapes and forms: high-performance computing (HPC) which is heavily focused on 
compute-intensive applications; high-throughput computing (HTC) which focuses 
on using many computing resources over long periods of time to accomplish its 
computational tasks; many-task computing (MTC) which aims to bridge the gap 
between HPC and HTC by focusing on using many resources over short periods of 
time; and data-intensive computing which is heavily focused on data 
distribution, data-parallel execution, and harnessing data locality by 
scheduling of computations close to the data. Today’s “Big Data” trend is 
generating datasets that are increasing exponentially in both complexity and 
volume, making their analysis, archival, and sharing one of the grand 
challenges of the 21st century. Not surprisingly, it becomes increasingly 
difficult to design and operate large scale systems capable of addressing these 
grand challenges. 

This journal Special Issue on Scientific Cloud Computing in the IEEE 
Transaction on Cloud Computing will provide the scientific community a 
dedicated forum for discussing new research, development, and deployment 
efforts in running these kinds of scientific computing workloads on Cloud 
Computing infrastructures. This special issue will focus on the use of 
cloud-based technologies to meet new compute-intensive and data-intensive 
scientific challenges that are not well served by the current supercomputers, 
grids and HPC clusters. The special issue will aim to address questions such 
as: What architectural changes to the current cloud frameworks (hardware, 
operating systems, networking and/or programming models) are needed to support 
science? Dynamic information derived from remote instruments and coupled 
simulation, and sensor ensembles that stream data for real-time analysis are 
important emerging techniques in scientific and cyber-physical engineering 
systems. How can cloud technologies enable and adapt to these new scientific 
approaches dealing with dynamism? How are scientists using clouds? Are there 
scientific HPC/HTC/MTC workloads that are suitable candidates to take advantage 
of emerging cloud computing resources with high efficiency? Commercial public 
clouds provide easy access to cloud infrastructure for scientists. What are the 
gaps in commercial cloud offerings and how can they be adapted for running 
existing and novel eScience applications? What benefits exist by adopting the 
cloud model, over clusters, grids, or supercomputers? What factors are limiting 
clouds use or would make them more usable/efficient? 


The topics of interest are, but not limited to, the application of Cloud in 
scientific applications: 

· Scientific application cases studies on Clouds 
· Performance evaluation of Cloud technologies 
· Fault tolerance and reliability in cloud systems 
· Data-intensive workloads and tools on Clouds 
· Programming models such as Map-Reduce 
· Storage cloud architectures 
· I/O and Data management in the Cloud 
· Workflow and resource management in the Cloud 
· NoSQL databases for scientific applications 
· Data streaming and dynamic applications on Clouds 
· Dynamic resource provisioning 
· Many-Task Computing in the Cloud 
· Application of cloud concepts in HPC environments 
· Virtualized High performance parallel file systems 
· Virtualized high performance I/O networks 
· Virtualization and its Impact on Applications 
· Distributed Operating Systems 
· Many-core computing and accelerators in the Cloud 
· Cloud security 

Authors are invited to submit papers with unpublished, original work to the 
IEEE Transactions on Cloud Computing, Special Issue on Scientific Cloud 
Computing. If the paper is extended from a workshop or conference paper, it 
must contain at least 50% new material with "brand" new ideas and results. The 
papers should not be longer than 14 double column pages in the IEEE TCC format. 
Papers should be submitted directly to TCC at 
https://mc.manuscriptcentral.com/tcc-cs, and "SI-ScienceCloud" should be 


· Kate Keahey, University of Chicago & Argonne National Laboratory, USA
· Ioan Raicu, Illinois Institute of Technology & Argonne National Lab., USA
· Kyle Chard, University of Chicago & Argonne National Laboratory, USA
· Bogdan Nicolae, IBM Research, Ireland


Email: sciencecloud2014-tcc-editors@xxxxxxxxxxxxxxxxxx
Website: http://datasys.cs.iit.edu/events/ScienceCloud2014-TCC/

Ioan Raicu, Ph.D.
Assistant Professor, Illinois Institute of Technology (IIT)
Guest Research Faculty, Argonne National Laboratory (ANL)
Data-Intensive Distributed Systems Laboratory, CS/IIT
Distributed Systems Laboratory, MCS/ANL
Editor: IEEE TCC, Springer JoCCASA
Chair:  IEEE/ACM MTAGS, ACM ScienceCloud, IEEE/ACM DataCloud
Cel:      1-847-722-0876
Office:   1-312-567-5704
Email:    iraicu@xxxxxxxxxx
Web:      http://www.cs.iit.edu/~iraicu/
Web:      http://datasys.cs.iit.edu/
LinkedIn: http://www.linkedin.com/in/ioanraicu
Google:   http://scholar.google.com/citations?user=jE73HYAAAAAJ