A Bounding Histogram Approach for Network Performance Analysis

We analyze the performance of a network under general traffics derived from traces. We apply stochastic comparisons in order to derive bounding histograms with a reduced size and complexity. We prove some stochastic monotonicity properties for the network elements, in order to derive bounds on the performance measures such as delays and losses. We show clearly that this approach provides an attractive solution as a trade-off between accuracy of the results and computation times. Moreover, we compare our results with an approximative method previously published, in order to show the accuracy of the bounds, and to highlight the benefits of our approach for network dimensioning.