Distributed Computer and Communication Networks 20th International Conference, DCCN 2017, Moscow, Russia, September 25–29, 2017, Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Vishnevskiy, Vladimir M. (Επιμελητής έκδοσης), Samouylov, Konstantin E. (Επιμελητής έκδοσης), Kozyrev, Dmitry V. (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Σειρά: Communications in Computer and Information Science, 700
• Θέματα: Computer science.; Computer communication systems.; Computer system failures.; Mathematical statistics.; Computer science > Mathematics.; Computer simulation.; Computer Science.; Computer Communication Networks.; Probability and Statistics in Computer Science.; System Performance and Evaluation.; Simulation and Modeling.; Math Applications in Computer Science.; Information Systems Applications (incl. Internet).

This book constitutes the refereed proceedings of the 20th International Conference on Distributed and Computer and Communication Networks, DCCN 2017, held in Moscow, Russia, in September 2017. The 39 full papers and the two short papers were carefully reviewed and selected from 176 submissions. The...

Πίνακας περιεχομένων:

• Computer and communication networks architecture optimization
• Control in computer and communication networks
• Performance and QoS/QoE evaluation in wireless networks
• Analytical modeling and simulation of next-generation communications systems
• Queuing theory and reliability theory applications in computer networks
• Wireless 4G/5G networks, cm- and mm-wave radio technologies
• RFID technology and its application in intellectual transportation networks
• Internet of things, wearables, and applications of distributed information systems
• Probabilistic and statistical models in information systems
• Mathematical modeling of high-tech systems
• Mathematical modeling and control problems
• Distributed and cloud computing systems, big data analytics.