Comparison of fair queuing algorithms with a stochastic approach

We compare fair queuing (FQ) algorithms with a novel approach based on the majorization theory of real valued vectors. We study the temporal evolution of the received normalized service of all backlogged sessions in order to give a better insight into the performance of a FQ policy than what worst-case measures can provide. As an application of this approach, we study the effect of the eligibility criterion on the service discrepancy. We show that a FQ policy with a large eligibility set scatters the normalized service less than another FQ policy with a smaller eligible set