Track: Resilient Digital Infrastructures

Track chairs

Aaron Ding (TU Delft)
Nirvana Meratnia (TU/e)
Maarten van Steen  (UT)

Track description

Digital infrastructures encompassing, among others, data centers, (physical) communication networks, and the management and control systems for physical infrastructures, are the backbone of our modern digital society. As industrial and public services become increasingly digitalized over these infrastructures, their resilience to intended and unintended disruptions has become critical. The growing societal demand for digital sovereignty, trust, and autonomy makes this challenge more urgent than ever. 

Resilience deals with ensuring dependability while disruptions occur. A resilient system continues to operate - remaining available, reliable, safe, secure, and maintainable - even when under stress or attacks. Yet, while much of today’s research and investment focuses on functionality and on preventing security breaches, far less attention is paid to how systems withstand and recover from disruptions when they occur.

This track aims to advance research and innovation on resilience in digital infrastructures, ensuring they remain dependable under adverse conditions. We seek to unite researchers and industry experts to uncover overlooked challenges, identify research gaps, and chart strategic pathways toward cross-sector collaboration.

This track will cover (but is not limited to):

Resilient Cloud, Edge & Data Center Architectures

- Fault-tolerant distributed computing, microservice resilience, and workload migration strategies.

Cybersecurity for Critical Digital Infrastructures

- New threat models, intrusion response automation.

Energy-Aware and Sustainable Resilience

- How energy constraints (e.g., in green datacenters or during power shortages) impact resilience—and how to mitigate it.

Network Resilience & Self-healing Systems

- Techniques like SDN/NFV-based reconfiguration, autonomous failover, and real-time fault detection.

AI assisted Autonomy for Digital Infrastructure Management

- Predictive maintenance, anomaly detection, and self-optimization.