(IF 5.900) Special issue on
The Converged Intelligent Networks are defined as telecommunication networks capable of integrating several radio and fixed accesses together with one management system. The prime example is the integration of different networks managed and controlled by one Mobile Network Operator (MNO). MNO may integrate WiFi, optical fiber and mobile network access for obtaining the highest efficiency of networking, such that the users’ expectation in regards to the connectivity may be fully satisfied.
The advantages of Converged Intelligent Networks are multiple: from the recompilation of networking management massive data and its use by providing Artificial Intelligence, through full separation of networking from services, until the introduction of new business services such as geolocalization or user-centric services.
The challenges are no less numerous since heterogeneous networks are difficultly manageable and require a management system built from the scratch. In addition, defined requirements for trusted networks must be implemented, so that connectivity may be conserved in handover through different technologies. On the one hand, technologies such as Software-Defined Networking, Network Functions Virtualization as well as new paradigms such as softwarization, containerization and edge computing make feasible the implementation of robust and scalable management systems. On the other hand, highest specialization of those technologies is key for adaptation to the massive information to be controlled in the network in very short timescales.
At the radio and wired access, the identified challenges include, among others, constant monitoring of resources and users, predictive algorithms, strong security approaches at the radio interface and trusted networking. Once again, the use of Artificial Intelligence and Machine Learning will play a crucial role in solving issues related with the complexity of multiple radio accesses. Artificial Intelligence provides insights from collected massive data and computes pattern identification and predictive resource usage in timescale of hundreds of milliseconds. However, Artificial Intelligence requires more research to adapt to the type and the frequency of data flows in advanced networks.
This Special Issue will address the major technological developments in both core and access of Intelligent (introducing Artificial Intelligence) networks, as well as industry and users’ needs in regards to Intelligent networks. We aim to address theoretical and practical issues in networking, ranging from basic concepts to research grade material, including future directions. Contributions to the following topics are of specific interest, but are not limited to:
Technologies for management of intelligent networks
Artificial Intelligence for network management
Modularized open networking platforms
Real-time networking data aggregation and processing
All-software approach; Beyond current solutions
Massive data in containerization and microservices
User-centrism paradigm in intelligent networks
Decentralization of data and data aggregation
Integration of Virtualized Network Functions and data
Advanced Radio technologies such as beamforming
Techniques for efficient radio data processing
Radio spectrum monitoring
Mobile users control
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Open submission : 10 July 2021
Submission deadline : 10 November 2021
Author notification : within 4 weeks after submission
Revised manuscript due : within 2 weeks after notification
Notification of acceptance : within 2 weeks after revision submission
Tentative accepted paper publication date : within 2 months after final version
Tentative SI paper collection and its web open: 1st Quarter, 2022 or 2nd Quarter, 2022
All submitted papers must be clearly written in excellent English and contain only original work. All papers must be submitted in an electronic format, e.g., PDF format (preferred) or MS Word. Manuscripts should follow the formatting of the sample manuscript and references. You can refer to the details in submission menu http://hcisj.com/submission/preparing_manuscript.php
All papers and some supplementary materials should be submitted through ScholarOne Manuscripts. The authors must select as “SI2021-02 Convergence Intelligent and Trusted Networks”. when they reach the “Article Type” step in the submission process https://mc04.manuscriptcentral.com/hcis
1. Jordi Mongay Batalla (Associate Professor), Warsaw University of Technology, Poland
2. Muhammad Imran, Federation University, Brisbane, Australia
3. Ruidong Li (Associate Professor), Kanazawa University, Japan
4. Constandinos X. Mavromoustakis, University of Nicosia, Cyprus