Dynamic class selection: From relative differentiation to absolute QoS

The relative differentiation architecture does not require per-flow state at the network core or edges, nor admission control, but it can only provide higher classes with better service than lower classes. A central premise in this context is that users with absolute QoS requirements should search dynamically for an appropriate class. We investigate this dynamic class selection (DCS) framework, and illustrate that, under certain conditions, DCS-capable users can meet absolute QoS requirements, even though the network only offers relative differentiation. For a single link model, we can examine whether it is feasible to satisfy all users, and when this is the case, compute the minimum acceptable class selection for each user. Users converge in a distributed manner to this minimum acceptable class, if the DCS equilibrium is unique. However, suboptimal DCS equilibria may also exist. Simulations of a delay-based DCS algorithm show the relation between class differentiation and DCS, and demonstrate how to control the trade-off between the performance and cost of a flow.