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To quantify the goodness of a configuration, we develop a probabilistic model of network configuration. A probabilistic graph then represents the statistical dependence in network configuration, and shows that self-configuration can be optimized if the graph has nested local dependence.

Near-Optimal Algorithm for Self-configuration of Ad-hoc Wireless Networks