ResilienceNetwork Resilience is Key to Surviving Compound Hazard Events
As weather extremes such as Superstorm Sandy, which swamped New York City’s subway system in 2012, increase in frequency and intensity and as cybercriminals ramp up attacks on technologies that tie together urban infrastructure systems, networks critical to the flow of data, people, goods, and services must be made more resilient to failure
As weather extremes such as Superstorm Sandy, which swamped New York City’s subway system in 2012, increase in frequency and intensity and as cybercriminals ramp up attacks on technologies that tie together urban infrastructure systems, networks critical to the flow of data, people, goods, and services must be made more resilient to failure, according to a team of scientists.
“To be able to quantify and compute system failure profiles is critical information that planners might need to make decisions in terms of how to recover these systems,” said Samrat Chatterjee, a data and operations research scientist at Pacific Northwest National Laboratory (PNNL) in Richland, Washington.
“If we are unable to characterize how the system is failing or might fail, how can we intervene and recover in an efficient manner?” he added.
Chatterjee is serving as principal investigator on a project with colleagues at Northeastern University in Boston, Massachusetts, that is developing computational frameworks to improve network resilience.
“What we mean by resilience in this context is robustness,” said project co-principal investigator Auroop Ganguly, a professor of civil and environmental engineering at Northeastern University. “Robustness means things will be slower to break, you will not lose service levels too fast or too much and, once something happens, you have a plan to recover efficiently, fast, and reliably.”
The team recently developed and implemented a generalizable computational framework to study the resilience of the multilayered London Rail Network to the compound threat of intense flooding and a targeted cyberattack. The team plans to use this generalizable computational framework to inform the design and engineering of other interdependent networks, including military installations.
Network-of-Networks
The team is particularly interested in understanding how changes in one network affect other interconnected networks, a so-called network-of-networks. The London Rail Network, for example, consists of the Underground subway, the Overground passenger trains, and the Dockland Light Rail. These three networks interconnect at shared nodes or rail stations.
If a bout of intense rain and flooding shutters a rail station, how might that closure ripple across the interconnected networks? If an adversary timed a cyberattack to follow the flooding, would the compound impact be disproportionate and greater than the sum of the parts?
