  The power of networks manifests itself in a highly non-linear amplification
of a number of effects, and their weakness - in propagation of cascading
failures. The potential systemic risk effects can be either exacerbated or
mitigated, depending on the resilience characteristics of the network. The
goals of this paper are to study some characteristics of network amplification
and resilience. We simulate random Erdos-Renyi networks and measure
amplification by varying node capacity, transaction volume, and expected
failure rates. We discover that network throughput scales almost quadratically
with respect to the node capacity and that the effects of excessive network
load and random and irreparable node faults are equivalent and almost perfectly
anticorrelated. This knowledge can be used by capacity planners to determine
optimal reliability requirements that maximize the optimal operational regions.
