  Traffic flows in a distributed computing network require both transmission
and processing, and can be interdicted by removing either communication or
computation resources. We study the robustness of a distributed computing
network under the failures of communication links and computation nodes. We
define cut metrics that measure the connectivity, and show a non-zero gap
between the maximum flow and the minimum cut. Moreover, we study a network flow
interdiction problem that minimizes the maximum flow by removing communication
and computation resources within a given budget. We develop mathematical
programs to compute the optimal interdiction, and polynomial-time approximation
algorithms that achieve near-optimal interdiction in simulation.
