Node-asynchronous Implementation of Rational Filters on Graphs

This paper considers a node-asynchronous implementation of rational ("IIR") filters on graphs, in which the nodes are assumed to wake up randomly and independently from each other, and communicate only with their immediate neighbors. The underlying graph is allowed to be directed, possibly with a non-diagonalizable adjacency matrix. Since the nodes are allowed to act independently, the proposed implementation is practical for very large or autonomous networks where synchronization is difficult to achieve. Furthermore, the proposed algorithm is 1-hop localized on the graph irrespective of the order of the filter. The method is shown to converge in the mean-squared sense under a boundedness assumption on the filter as well as the graph operator. The result follows from the convergence of a more general randomized asynchronous state recursion, which is also presented in this paper. The algorithm is simulated on a random geometric graph, which numerically verifies the convergence.