5G και V&V: εκτίμηση απόδοσης σε 5ης γενιάς υπηρεσίες δικτύων - Στοχευμένες δοκιμές επικύρωσης και επαλήθευσης

Τούλουπου, Μάριος

5G and V&V: performance prediction in 5th generation networks – Targeted verification and validation

Master Thesis

Author

Τούλουπου, Μάριος

Date

2019-03

Abstract

The Convergence to 5G, IoT and advanced data analysis is going to disrupt the Information and Communication Technology (ICT) ecosystem. The combined effect of these technologies will pave the way for new business models, technological innovation and thousands of opportunities for applications in all industrial areas based on telecoms and IT services. 5G promises to enable intelligent network and application services with connectivity to remote sensors, huge amounts of IoT data and high-definition data transmission. Analytical data will also no longer be a thought but will play an important role in the evolution of 5G standards that will allow intelligence throughout the network, applications and businesses. Therefore, this diploma thesis focuses on 5th generation networks presenting the technological developments and opportunities created with them as well as the technical barriers to this path. Also, focusing on the traffic generated by the 5th generation applications, there is a need for data analysis and applications’ performance estimation. As a result, in order to enhance the validation and verification (V & V) of different network services (NS) on heterogeneous platforms, the analysis of generated tracking data, belonging to network services running on a software-defined network (SDN), is presented. Additionally, a data analysis and correlation calculation approach is also presented where service developers can benefit from the key components of the mechanism to understand the behavior of their service and thus optimize the V&V testing before sending the service to the production.

Postgraduate Studies Programme

Προηγμένα Συστήματα Πληροφορικής

Department

Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Ψηφιακών Συστημάτων

Number of pages

Language

Greek

URI

https://dione.lib.unipi.gr/xmlui/handle/unipi/11887

Collections

Τμήμα Ψηφιακών Συστημάτων

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