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The capacity (or maximum flow) of an unicast network is known to be equal tothe minimum s-t cut capacity due to the max-flow min-cut theorem. If thetopology of a network (or link capacities) is dynamically changing or unknown,it is not so trivial to predict statistical properties on the maximum flow ofthe network. In this paper, we present a probabilistic analysis for evaluatingthe accumulate distribution of the minimum s-t cut capacity on random graphs.The graph ensemble treated in this paper consists of weighted graphs witharbitrary specified degree distribution. The main contribution of our work is alower bound for the accumulate distribution of the minimum s-t cut capacity.From some computer experiments, it is observed that the lower bound derivedhere reflects the actual statistical behavior of the minimum s-t cut capacityof random graphs with specified degrees.

ieice transactions on fundamentals of electronics, communications and computer sciences/ieice transactions on fundamentals of electronics, communications and computer science

An Analysis on Minimum s-t Cut Capacity of Random Graphs with Specified Degree Distribution