Appel: FGCS, Special Issue on Intelligent Big Data Processing

[Thierry Hamon]

Date: Wed, 10 Oct 2012 15:31:59 +0800
From: cfp at grid.chu.edu.tw
Message-Id: <201210100731.q9A7Vxr4004958 at grid.chu.edu.tw>
X-url: http://www.journals.elsevier.com/future-generation-computer-systems/calls-for-papers/special-issue-on-intelligent-big-data-processing/


Future Generation Computer Systems (http://ees.elsevier.com/fgcs/)

Special Issue on Intelligent Big Data Processing

http://www.journals.elsevier.com/future-generation-computer-systems/
calls-for-papers/special-issue-on-intelligent-big-data-processing/


== Overview ==

Nowadays, data comes from sensors, lab experiments, simulations,
individual archives, enterprise and Internet in all scales and
formats. This data flood has outpaced our capability to process,
analyze, store and understand these datasets. Such rapid expansion is
also accelerated by the dramatic increase in acceptance of social media
and networking applications. Furthermore, It can be foreseen that
Internet of things (IoT) applications will raise the scale of data to an
unprecedented level. People and devices (from home coffee machines to
cars, to buses, railway stations and airports) are all loosely
connected. Trillions of such connected components will generate a huge
data ocean, and valuable information must be discovered from the data to
help improve quality of life and make our world a better place. This
special issue intends to tackle such data deluge issues intelligently,
efficiently and effectively. Areas of interest for this special issue
include the following topics:

- Intelligent data mining techniques
- Dynamic data redistribution
- Scalable and distributed algorithms
- New programming models for large data
- Locality aware data processing
- NoSQL
- Data filtering techniques for Internet of Things
- DaaS, Data as a Service
- MapReduce in hybrid clouds
- Asynchronous data processing
- Opportunistic data processing in hybrid clouds
- Intelligent storage and load balancing
- Data migration and synchronization (between private and public clouds)
- Multi-tier MapReduce programming model
- Dynamic Mapper/Reducer join/leave
- Data decomposition base on GPU / CPU availability
- Dynamic provisioning for big data processing
- System Issues related to large datasets

== Schedule ==

Manuscript due date: December 20, 2012
First round notification: March 1st, 2013
Submission due date of revised paper: April 15, 2013
Notification of acceptance: May 15, 2013
Submission of final revised paper: June 10, 2013
Publication: September 2013 (tentative)

== Submission & Review Instruction ==

Submitted articles must not have been previously published or currently
submitted for journal publication elsewhere. Submissions must be
directly sent via the FGCS submission web site at
http://ees.elsevier.com/fgcs/login.asp (please select the track - SS:
Intelligent Big Data - Hsu).

Paper submissions must conform to the layout and format guidelines in
Future Generation Computer Systems. For a full and complete Guide for
Authors, please refer to: http://www.elsevier.com/fgcs

Each submitted paper will be reviewed by at least three Editorial
reviewers

Criteria and Evaluation for acceptance of paper:
- Significance to the journal's audience
- Relevance to this special issue
- Overall recommendation on the paper
- Optional confidential comments to the Editorial Committee

Quality of the paper including originality, technical depth,
significance of results, adequacy of priori works referenced, overall
organization, clarity and readability, satisfactory English writing,
sufficient support for assertions and conclusion, appropriate title,
abstract adequately summarizes the paper, introduction provides proper
orientation, clear tables and figures.

Guest Editors

Ching-Hsien (Robert) Hsu
Department of Computer Science and Information Engineering,
Chung Hua University, Taiwan
Email: chh at chu.edu.tw
http://www.chu.edu.tw/~chh

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