In the face of natural disasters or crises, communication networks play a vital role in ensuring efficient disaster management and mitigation. However, the fragility of individual communication technologies and networks during such events often disrupts critical information flow, posing significant challenges for response teams and affected communities.
The emergenCity center addresses this critical need by investigating how individual communication networks can be made more resilient to form a cohesive and robust "disaster network." While advancements in individual network resilience are vital, the key challenge lies in enabling these independent networks to collaborate and function as a complex network of networks. Due to the potentially highly different capabilities and properties of different networks, their partial availability, and lack of a global information state, routing decisions cannot always be optimal or pre-calculated.
This thesis aims to address these challenges by combining theoretical analysis, modeling, and simulations to explore how various network types — e.g., IoT networks, satellite networks, or UAV-based networks — can be combined by using resilient routing decisions based on limited or error-prone information.
This thesis will:
- Explore state-of-the-art research literature and the requirement space
- Design and validate approaches for complex decision-making within packet routing in Disruption-Tolerant Networks
- Implementation and simulative evaluation of approaches and comparison against baseline approaches, considering varying network configurations, communication links, topologies, and more
- Explore the impact of routing decisions within the disaster network of networks, analyzing resilience, tradeoffs, and the influence of imperfect information
The outcomes of this thesis will provide valuable insights into designing a resilient communication framework capable of sustaining connectivity during crises, contributing to emergenCity’s goals of disaster resilience in complex crises.
Skills/Prerequisites
- Good programming skills in Python or other OOPLs
- Knowledge of (wireless) communication networks, wireless routing protocols
- Knowledge on Delay-/Disruption-Tolerant Networks (DTNs) is not required but will be learned
- Basic knowledge in simulations and modeling, LaTeX, Git, data analysis is helpful but not required and will be learned