-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] CFP on IoT - IJITSA - Aug.31.2016 Datum: Mon, 27 Jun 2016 12:49:22 -0500 (CDT) Von: mmora@securenym.net An: aisworld@lists.aisnet.org Kopie (CC): luiz-angelo.steffenel@univ-reims.fr
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
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