On Distributed Optimization Over Random Independent Networks

We consider the averaging-based distributed optimization over random independent but time-varying networks where we generalize the results for independently and identically distributed (i.i.d.) networks to independent networks. In this paper, we show that under some assumptions on average connectivity the averaging-based distributed optimization methods still work for independent random networks when the averaging weight matrices are column-stochastic in-expectation. This result has interesting implications including implications on the robustness of the averaging-based distributed optimization methods to link-failure.