Authors are encouraged to submit their papers (6-8 pages) in Russian or English language via the online registration system uConfy.com. The accepted papers will be published in the Conference Proceedings volume (included into the Russian Science Citation Index) prior to the beginning of the Conference.

For your convenience, we made available the DCCN templates in the scientific authoring platform Overleaf:

After a peer review and plagiarism check, authors of selected submissions in English, recommended by the Program Committee, will be invited to submit their extended papers (12-15 pages in Springer LNCS template). After a second round of review the accepted extended papers will be published by Springer (approve pending) as a stand-alone volume of selected extended papers (indexed in Scopus and Web of Science).

Please note, that peer review is double-blinded. Authors are required to remove their names, affiliation and any other information that may be used to identify them prior to review. In case the submission is not blinded, it may be rejected before the review.

Topics include, but are not limited to the following fields:

• Communication networks algorithms and protocols
• Wireless and mobile networks
• Computer and telecommunication networks control and management
• Performance analysis, QoS/QoE evaluation and network efficiency
• Evolution of wireless networks toward 5G
• Centimeter- and millimeter-wave radio technologies
• High-altitude telecommunications platforms
• Quantum Information and quantum communication
• Machine learning, big data, artificial intelligence
• Performance analysis, QoS/QoE evaluation and network efficiency
• Analytical modeling and simulation of communication systems
• Probabilistic and statistical models in information systems
• Queuing theory and reliability theory applications
• Quantum Information and quantum communication
• Machine learning, big data, artificial intelligence
• Internet of Things and Fog Computing
• Cloud computing, distributed and parallel systems
• Security in infocommunication systems
• Machine learning, big data, artificial intelligence