[hpc-announce] CFP - IEEE TCC Special Issue on "Big Data Computing on Clouds"
jinjun.chen at gmail.com
Wed Mar 26 00:08:24 CDT 2014
Call for Papers:
IEEE Transactions on Cloud Computing Special Issue on "Big Data Computing
Big data is an emerging paradigm applied to datasets whose size or
complexity is beyond the ability of commonly used computer software and
hardware tools. Such datasets are often from various sources (Variety) yet
unstructured such as social media, sensors, scientific applications,
surveillance, video and image archives, Internet texts and documents,
Internet search indexing, medical records, business transactions and web
logs; and are of large size (Volume) with fast data in/out (Velocity). More
importantly, big data has to be of high value (Value) and establish trust
in it for business decision making (Veracity). Various technologies are
being discussed to support the handling of big data such as massively
parallel processing databases, scalable storage systems, cloud computing
platforms, and MapReduce.
As estimated by IDC, by 2020, about 40% data globally would be touched with
Cloud Computing. Besides, Cloud Computing provides strong storage,
computation and distributed capability in support of Big Data processing.
Therefore, there is a strong demand to investigate various challenges about
how to support Big Data processing by facilitating Cloud Computing
potential. This special issue will focus on this challenging topic.
Original and unpublished high-quality research results are solicited to
explore various challenging topics which include, but are not limited to:
· Cloud Architecture for Big Data
· Resource scheduling and SLA for Big Data on Cloud
· Storage and computation management in Cloud for Big Data
· Large-scale data intensive workflow in support of Big Data
processing on Cloud
· Multiple source data processing and integration on Cloud
· Virtualisation and visualisation of Big Data on Cloud
· Fault tolerance and reliability for Big Data processing on Cloud
· MapReduce with Cloud for Big Data processing
· Big data application workflow management on Cloud
· Distributed file storage system with Cloud for Big Data
· Inter-cloud technology for Big Data
· Security, privacy and trust in Big Data processing on Cloud
· Green, energy-efficient models and sustainability issues in Cloud
for Big Data processing
· Cloud infrastructure for social networking with Big Data
· User friendly Cloud access for Big Data processing
· Innovative Cloud data centre networking for Big Data
· Wireless and mobility support in Cloud data centre for Big Data
· Cloud and Big Data for Smart and Sustainable Cities
Submission due date: November 15, 2014
Notification of acceptance: March 15, 2015
Submission of final manuscript: May 15, 2015
Publication date: 2nd Quarter, 2015 (Tentative)
*Submission & Major Guidelines*
The special issue invites original research papers that make significant
contributions to the state-of-the-art in "Big Data Computing on Clouds".
The papers must not have been previously published or submitted for
journal or conference publications. However, the papers that have been
previously published with reputed conferences such as *IEEE BDSE 2014 (Big
Data Science and Engineering - http://www.swinflow.org/confs/bdse2014/
<http://www.swinflow.org/confs/bdse2014/>*) could be considered for
publication in the special issue if they contain significant number of "new
and original" ideas/contributions along with more than 49% brand "new"
material. Every submitted paper will receive at least three reviews. The
editorial review committee will include well known experts in the area.
Submissions must be directly submitted via the IEEE TCC submission web site
at https://mc.manuscriptcentral.com/tcc-cs, and must follow instructions
for formatting and length listed there.
For additional information, please contact Jinjun.Chen at gmail.com.
*Selection and Evaluation Criteria*
- Significance to the readership of the journal
- Relevance to the special issue
- Originality of idea, technical contribution, and significance of the
- Quality, clarity, and readability of the written text
- Quality of references and related work
- Quality of research hypothesis, assertions, and conclusion
Rajkumar Buyya, The University of Melbourne, Australia
Jinjun Chen (Contact Person), Jinjun.Chen at gmail.com, University of
Technology Sydney, Australia
Ivan Stojmenovic, ivan at site.uottawa.ca, University of Ottawa, Canada
Irena Bojanova, ibojanova at umuc.edu, University of Maryland University
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