Manuscripts can be submitted continuously until the deadline. Once a paper is submitted, the review process will start immediately. Accepted papers will be published continuously in the journal. All accepted papers will be listed together in an online Special Issue published in the journal website. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.
The pervasive presence of data originating from the coupling of mobile technologies and wireless networks, urban and socio-physical systems, industrial equipment and people, has led to massive data distribution at the edge of the networked environments and to an increasing interest in solutions which provide efficient and distributed data management. At the core of this vision lies the emergence of data-driven networks and cyber-physical systems saturated with pervasive sensing, computing, and wireless communication capabilities that ideally support the needs of individuals, societies and industries.
In this context, the emerging concept of Data Distribution in the Pervasive and Industrial Internet is increasingly being recognized as a systematic conceptual framework for designing, testing, and analyzing systems and algorithms that support the upcoming cyber-physical convergence. Submissions to this Special Issue can be analytical, empirical, technological, methodological, or a combination of those. Contributions on strong data-oriented systems engineering backed by solid and appropriate evaluations are strongly encouraged. The impact of the contributions should be demonstrated in the context of the data-related aspects in the pervasive and industrial internet.
Research contributions are solicited in all application areas pertinent to industrial and pervasive data distribution, including but not limited to:
Data distribution in the pervasive internet, where the ambient intelligence of network devices embedded in the environment, as well as urban and socio-physical analytics can facilitate a constant and unobtrusive data management and distribution. Indicative areas of interest include:
Data distribution and management in the pervasive internet
Clouds, cloudlets, fog computing, device-to-device coordination
Smart spaces and intelligent environments supporting distributed data
Data-enabled mobile and wearable sensing and computing
Cognitive computing techniques on the edge of data-intensive networks
Data-oriented social cyber-physical computing and human in the loop
Data-focused crowdsensing and user analytics
Data privacy and security preserving algorithms and techniques in the pervasive internet
Data distribution in the industrial internet, where intelligent entities can exchange and manage distributed data in order to achieve improved performance for both the cyber and the physical components. Indicative areas of interest include:
Data distribution and management in the industrial internet
Networking protocol stacks and standardization for efficient data management
Data distribution with industrial cloud and edge computing
Data-oriented networked control, distributed optimization, and distributed learning
Data-driven industrial internet robotics and autonomous systems
Data-intensive cyber-physical processes and networks
Data distribution solutions which satisfy the Industry 4.0 requirements
Data privacy and security preserving algorithms and techniques in the industrial internet
Submission Deadline: 15 Sep 2019
Final Acceptance Notification: 15 Feb 2020
Estimated Publication: May 2020
Please see http://www.elsevier.com/locate/comcom for preparation guidelines and visit https://www.evise.com/profile/#/COMCOM/login to submit your manuscript. To ensure that all manuscripts are correctly identified for inclusion into the special issue, please select \”VSI:Data Pervasive Internet\” when you reach the Article Type step in the submission process. For further information, please contact the guest editors.
Dr. Theofanis P. Raptis, National Research Council of Italy
Assoc. Prof. Georgios Z. Papadopoulos, IMT Atlantique
Prof. Archan Misra, Singapore Management University
Prof. Salil Kanhere, UNSW Sydney