fgcs 2012 - Special Issue on "Innovative Methods and Algorithms for Advanced Data-Intensive Computing"

Future Generation Computer Systems (http://www.elsevier.com/locate/fgcs/),
Elsevier (http://www.elsevier.com/wps/find/homepage.cws_home), Special Issue
on "Innovative Methods and Algorithms for Advanced Data-Intensive Computing"
(http://si.deis.unical.it/cuzzocrea/FGCS2012/)
Chair

Alfredo Cuzzocrea (http://si.deis.unical.it/cuzzocrea/), ICAR-CNR and
University of Calabria, Italy
Aim and Scope

Advanced data-intensive computing represents an active area of research that
spans across a significant number of research topics ranging from
traditional parallel and distributed computing to recent Grid and Cloud
computing. All these high-performance paradigms share a common emphasis that
focuses on the issue of effectively and efficiently representing, managing
and distributing large-size and large-scale data that populate their
internal layers. This conveys to the well-known term "data-intensive
computing", which represents an emerging challenge in next-generation
computing systems.
Data-intensive computing has recently been of great interest for the
research community, mainly driven by modern research initiatives such as big
data management, analytics over large-scale data, very-large scientific data
management, social network data management, and so forth. There exists a
wide range of application scenarios where data-intensive computing is
relevant: scientific data management, bio-medical data management, sensor
and stream data management, environmental data management, and so forth.
While traditional challenges of sensor and stream processing
(bounded-memory, single-pass processing, blocking query operators,
multi-rate arrivals, and so forth) affect managing, updating and querying
exact sensor and stream databases, additional challenges arise when dealing
with novel uncertain sensor and stream databases. Hence, innovative models,
algorithms and techniques for managing, updating and querying uncertain
sensor and stream databases must be devised, perhaps embedding probabilistic
or statistical approaches.
Managing these kinds of data poses critical and still-unsolved issues,
mostly represented by the enormous size of data and the exponential
scaling-up of data over growing-in-size inputs and requirements. A reliable
solution to these issues comes from the usage of advanced computational
paradigms, like MapReduce, and infrastructures, like Clouds. A necessary
step towards the successfully achievement of this goal is represented by the
need for innovative methods and algorithms for advanced data-intensive
computing, as classical proposals appeared in traditional areas like
parallel and distributed computing are clearly inadequate to cope with the
requirements dictated by modern data-intensive scenarios.
With these goals in mind, the proposed Future Generation Computer Systems
(FGCS) special issue will cover theoretical as well as practical aspects of
models and algorithms for advanced data-intensive computing on
high-performance computational infrastructures like Grids and Clouds.
Relevant research areas for the proposed FGCS special issue include, but are
not limited to, the following ones:
- foundations of advanced data-intensive computing;
- advanced data-intensive computing models;
- advanced data-intensive computing methodologies;
- advanced data-intensive computing techniques;
- advanced data-intensive computing algorithms;
- pervasive data-intensive computing
- high-performance advanced data-intensive computing in innovative contexts
like streams, sensors, mobile environments and social networks;
- innovative scenarios of advanced data-intensive computing (e.g.,
scientific data, biomedical data, statistical data etc);
- theoretical aspects of advanced data-intensive computing;
- privacy aspects of advanced data-intensive computing;
- security aspects of advanced data-intensive computing;
- load-balancing issues in advanced data-intensive computing;
- scheduling paradigms for advanced data-intensive computing;
- scalable data-intensive computing models;
- scalable data-intensive computing algorithms;
- disk-based models for advanced data-intensive computing;
- disk-based algorithms for advanced data-intensive computing;
- cluster-based models for advanced data-intensive computing;
- cluster-based algorithms for advanced data-intensive computing;
- cloud-based models for advanced data-intensive computing;
- cloud-based algorithms for advanced data-intensive computing;
- service-oriented-based models for advanced data-intensive computing;
- service-oriented-based algorithms for advanced data-intensive computing;
- P2P-oriented advanced data-intensive computing;
- Map-Reduce-based advanced data-intensive computing.
Schedule (Tentative)

Submission of full papers: April 15, 2012
First decision notification: July 15, 2012
Submission of revised papers: August 15, 2012
Final decision notification: September 15, 2012
Final materials to Elsevier: October 15, 2012
Estimated publication date: 2012
Submission Guidelines and Instructions

All manuscripts will be rigorously refereed by at least three reviewers
among people of widely-recognized expertise. Submission of a manuscript to
this special issue implies that no similar paper is already accepted or will
be submitted to any other conference or journal.
Author guidelines for preparation of manuscript can be found at:
http://ees.elsevier.com/fgcs/
All manuscripts and any supplementary material should be submitted through
Elsevier Editorial System (EES). Authors must select "SI:
Met.&Alg.Adv.D-Int.Cmp.-Alfredo" when they reach the "Article Type" step in
the submission process. The EES Web site for FGCS is available at:
http://ees.elsevier.com/fgcs/
For more information and any inquire, please contact Alfredo Cuzzocrea
(http://si.deis.unical.it/~cuzzocrea/) at cuzzocrea-AT-si.deis.unical.it