Risk-adaptive strategic network protection in disaster scenarios.

The dynamic behaviour of natural disasters and their probabilistic failure pattern indicates a need for a dynamic, risk-based protection approach to reduce the number of disrupted connections in the network. Appropriate traffic protection against a time-varying destructive phenomenon serves to prevent damage before it occurs. In this case, the level of risk for traffic routes should be evaluated and the flow should be rerouted to more reliable paths prior to failure. The high-risk paths can be identified based on appropriate decision parameters in a preventive protection scheme as an effective dynamic probabilistic solution to address large-scale failure scenarios. In this paper, we study the effect of dynamic tuning of decision parameters on network performance and discuss their impact on traffic protection. Furthermore, we develop a self-adapting preventive approach to enhance traffic protection with respect to disaster behaviour and undamaged, operational network resources. The proposed approach dynamically adjusts rerouting decision parameters to provide an appropriate level of protection while the impact domain of the natural disaster expands through the region and increases the risk of failure for network components. Our simulations, conducted in real-world topologies, confirm the feasibility of the proposed approach for traffic protection in large-scale failure scenarios.