Distributed network decomposition: A probabilistic greedy approach

In this paper, we propose a novel distributed network decomposition algorithm with the aid of the factor graph model and the max-product algorithm, which aims to achieve minimum cut weight. Its effectiveness is testified for general graph partition as well as distributed inference in wireless networks. Our algorithm is fully distributed, simple in computation, and readily extensible, thus providing a potentially powerful, data-independent clustering scheme for a wide range of data processing and networking applications.