Background

Today, low bandwidth networks such as GSM, providing less than 200 Kbps are being used to transmit train control information. Moreover, despite trains may use multiple on-board technologies to provide users with an internet connection (e.g., repeaters, access points), they fail in their attempt as these connections are characterized by having low throughput (less than 2 Mbps) and frequent service interruptions. This motivates the exploration of networks enabling train control and on-board data communications under mobility scenarios with high reliability and controlled latency.

Research question

The goal of this work is to analyze the robustness of the Rail Data Network and its variants to identify the most robust alternative. The topologies and traffic matrix will be given. The plan is to develop robustness surfaces [1] to understand the strengths and weaknesses of different networks combinations.

The results from this work can be useful to get an insight on requirements for Smart Transportation Systems, that may in turn be useful for cementing the basis of other scenarios such as: Autonomous Driving and Tele-Operated Driving.

 References

[1] Manzano, M., Sahneh, F., Scoglio, C., Calle, E. and Marzo, J.L., 2014. Robustness surfaces of complex networks. Scientific reports, 4(1), p.6133.

[2] Digitale Schiene Deutschland. Last visit on 13.12.2021 https://digitale-schiene-deutschland.de/FRMCS-5G-Datenkommunikation

[3] 5G-Rail FRMCS. Last visit on 13.12.2021 https://5grail.eu/frmcs/

Requirements

Basic knowledge in:

• Python
• Communication Network Reliability course at LKN or equivalent knowledge.

Please send your CV and transcript of records.

Availability is the probability that a device performs its required function at a particular instant of time.

In most networks, the components are brought from different manufacturers. They have different availabilities. Network operators prefer having reliable components handling more traffic. This ensures the robustness of the network. So, assigning appropriate manufacturers to the components in the topology to guarantee maximum availability is essential.

In this work, the student uses centrality metrics to identify the critical nodes and assign manufacturers based on these metrics.

Mandatory:

• Kommunikationsnetze course at LKN
• Python

Availability is the probability that a device performs its required function at a particular instant of time.

In most networks, the components are brought from different manufacturers. They have different availabilities. Network operators prefer having reliable components handling more traffic. This ensures the robustness of the network. So, assigning appropriate manufacturers to the components in the topology guaranteeing 
a) maximum availability, and 
b) load balancing on the nodes
is essential.

For a fixed topology and known traffic, how can the components be assigned to manufacturers to maximise availability and balance load on nodes?

Mandatory:

• Communication Network Reliability course/ Optical Networks course at LKN
• Python

Preferred:

• Knowledge of Linear Programming and/or nonlinear programming