Measuring cascade effects in interdependent networks by using effective graph resistance
Tauch, S; Liu, W; Pears, R
Abstract
Understanding the correlation between the underlie
network structure and overlay cascade effects in the interdependent
networks is one of major challenges in complex network
studies. There are some existing metrics that can be used
to measure the cascades. However, different metrics such as
average node degree interpret different characteristic of network
topological structure, especially less metrics have been identified
to effectively measure the cascading performance in interdependent
networks. In this paper, we propose to use a combined
Laplacian matrix to model the interdependent networks and their
interconnectivity, and then use its effective resistance metric as an
indicator to its cascading behavior. Moreover, we have conducted
extensive comparative studies among different metrics such as
average node degree, and the proposed effective resistance. We
have found that the effective resistance metric can describe more
accurate and finer characteristics on topological structure of
the interdependent networks than average node degree which
is widely adapted by the existing research studies for measuring
the cascading performance in interdependent networks.