Call for Papers
IEEE Transactions on Cloud Computing
Special Issue on Scientific Cloud Computing
IMPORTANT DATES
Paper Submissions Due: July 31, 2014
First Round Decision: September 30,2014
Major Revisions Due (if neccesary): October 31, 2014 Final Decision:
December 1, 2014 Journal Publication: TBD
OVERVIEW
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?
TOPICS
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
SUBMISSION INSTRUCTIONS
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
selected.
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
CONTACT
Email: sciencecloud2014-tcc-editors@datasys.cs.iit.edu
Website: http://datasys.cs.iit.edu/events/ScienceCloud2014-TCC/
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