Dear colleagues in AISWorld in the IT engineering research stream!
This CFP could be of great interest for some of you. Thanks for your
consideration and dissemination. Sincerely,
Dr. Mora / EiC of IJITSA / ACM Senior Member

----------------------------------------------------------------------
Calls for Papers (special): International Journal of Information
Technologies and Systems Approach (IJITSA)

Special Issue On: Computing Challenges on IoT and Pervasive Systems
Submission Due Date
8/31/2016

Guest Editors
Luiz Angelo Steffenel (University of Reims Champagne-Ardenne, France)
Manuele Kirsch Pinheiro (University of Paris 1 Panthéon-Sorbonne, France)

Introduction

In the next 25 years, most of the things and devices we interact with will
be linked to a global computing infrastructure (Broy & Schmidt,2014). This
massive integration of communicating capabilities on physical objects
symbolizes the advent of the Internet of Things (IoT). The IoT represents
a new tendency on IT industry, in which physical environment is populated
by interconnected and communicating objects, capable of interacting with
each other and with the environment itself. The strength of this concept
lies in the seamlessly integration of sensors, actuators and other devices
in the environment in a large scale, allowing interacting and collecting
information from this. According to Sundmaeker et al. (2010), things on
the IoT are expected to become active, participating in business,
information and social process.

Several factors are contributing the increasing development of IoT, among
them the cost of sensors, bandwidth and processing power that have decline
in the last years (Jones, 2014). Thanks to current technology and its
reducing costs, IoT is already becoming a reality. Nowadays, it is
possible to put a wireless interface on almost all every day object,
making possible interaction between them (Paridel et al., 2010). Such
communicating capabilities open countless opportunities in different
application domains, like health-care and smart cities, just to name a
very few.

One of the most important outcomes of IoT is the possibility of creating
an unprecedented amount of data, which has to be stored and used
intelligently for smart monitoring and actuation (Gubbi et al., 2013).
This ability of sensing physical phenomena or triggering actions on the
physical reality is what differentiates IoT from traditional networked
systems. IoT focus is on data and information, since, from the conceptual
standpoint, IoT is about entities acting as providers and/or consumers of
data related to the physical world (Miorandi et al., 2012). The challenge
therefore concerns how to opportunistically explore collected information
from IoT environment. Appropriate data analysis and data mining techniques
are necessary in order to explore IoT data, but analyzing such data
represents a scalability issue, both on the data volume and on its
distribution over the environment. The collected data is also
characterized by its dynamicity and its heterogeneity, which represents an
interesting challenge for data analysis techniques.

To fully exploit the potential of billions of loosely connected devices,
IoT applications and systems must face communication, data management,
security and computing challenges without precedent. Currently, computing
IoT data is been performed mostly on cloud computing infrastructures since
storage and computing power of IoT devices is often limited. Indeed, cloud
computing are offering powerful and flexible capabilities for running IoT
data services and applications by using Internet infrastructure (Serrano
et al., 2013). By using cloud platforms, it is possible to analyze
increasingly volume of data, following an on-demand model, in which new
resources can be easily allocated according application needs. Despite its
advantages, cloud platforms have also some important drawbacks. Among
these, we may cite security and privacy concerns, as well as network
latency (Hofmann & Woods, 2010). Indeed, the transfer of large volume of
data from IoT environments to cloud platforms may be significantly costly
and time consuming. As response time is a potential source of problems for
delay-sensitive applications (idem, 2010), some recent works focus on how
to leverage the available resources closer to the user through the use of
pervasive grids, alone or in collaboration with distant cloud
infrastructures. Pervasive grids seamlessly integrate pervasive
sensing/actuating instruments and devices together with classical high
performance systems (Parashar & Pierson, 2010), and represent an
opportunity to deploy computing and data analysis tasks in computing
resources available around IoT devices, minimizing data transfer over
distant network. Pervasive grids offer the possibility of consuming
computing power and storage from any available resources, independently of
its nature, from small devices like Raspberry Pi up to clusters or cloud
infrastructures (Steffenel & Kirsch-Pinheiro, 2015).

In spite of the recent advances on IoT, there are still several challenges
to be tackled when carrying computations, data analysis and data
management in systems at the IoT scale. In this special issue, we are
seeking new and unpublished work in the domain of IoT and pervasive
systems targeting cloud and pervasive platforms for IoT. More
specifically, we look for network, data management and data mining
techniques adapted to the dynamicity and scalability of IoT.

Objective

This special issue aims at promoting and disseminating the recent advances
in the field of computing and data management on Internet of Things (IoT)
and Pervasive Systems, both at academic and industry level, with a special
focus on dynamicity and scalability issues.

Recommended Topics
Topics to be discussed in this special issue include (but are not limited
to) the following:

    Big Data and Data analytics for IoT on clouds or Pervasive Systems
    Data-intensive computing on hybrid infrastructures (clusters, clouds,
grids, P2P)
    Challenges in big data storage and processing on heterogeneous
environments
    Pervasive Grids, Mobile Edge Computing, Fog Computing
    Algorithms for big data and data mining on Pervasive Systems
    Mining and recommendation techniques for Pervasive Systems
    Pervasive computing and IoT applied to Smart Cities
    Architectural designs methods for IoT and Pervasive Systems
    Programming models, including MapReduce, extensions, and new models
applied to Pervasive Systems
    Scalability and elasticity in IoT and Pervasive Systems
    Fault-tolerance and reliability in IoT and Pervasive Systems
    Performance analysis of tools and applications in IoT and Pervasive
Systems
    Scheduling and resource management in IoT and Pervasive Systems
    Architectures frameworks and standards for IoT Systems
    Agile development systems methodologies for IoT and Pervasive Systems
    Software-defined networks for IoT and Pervasive Systems

Submission Procedure
Researchers and practitioners are invited to submit papers for this
special theme issue on Computing Challenges on IoT and Pervasive Systems
on or before August 31th, 2016. All submissions must be original and may
not be under review by another publication. INTERESTED AUTHORS SHOULD
CONSULT THE JOURNALS GUIDELINES FOR MANUSCRIPT SUBMISSIONS at
http://www.igi-global.com/Files/AuthorEditor/guidelinessubmission.pdf. All
submitted papers will be reviewed on a double-blind, peer review basis.
Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:
Dr. Luiz Angelo Steffenel
Lead Guest Editor
International Journal of Information Technologies and Systems Approach
(IJITSA)
E-mail: luiz-angelo.steffenel@univ-reims.fr
Submit a Manuscript to: Computing Challenges on I...

_______________________________________________
AISWorld mailing list
AISWorld@lists.aisnet.org

Betreff:	[AISWorld] CFP: special issue on IoT (technical side !) in IJITSA journal
Datum:	Wed, 18 May 2016 10:50:15 -0500 (CDT)
Von:	mmora@securenym.net
An:	aisworld@lists.aisnet.org <aisworld@lists.aisnet.org>
Kopie (CC):	Angelo.Steffenel@univ-reims.fr, Manuele.Kirsch-Pinheiro@univ-paris1.fr