Extending the power of backpressure to correlated traffic

We study the impact of time-correlated arrivals on the performance of backpressure policy for stochastic network control. The arrival process considered in this work is fairly general in the sense that it may exhibit short/long-range dependence depending on the asymptotic shape of the autocorrelation function. In this paper, we show that that the backpressure policy stabilizes the network whenever the arrival rate vector is inside the stability region even though the arrivals have finite-length memory or infinite-length memory with monotonically decreasing autocorrelation functions. Apart from the stability, the effect of correlations appears in the upper bound on average network delay.