Abstract

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 the relative differentiation architecture is that users with an absolute QoS requirement can dynamically search for a class which provides the desired QoS level. In the first part of this paper, we investigate this Dynamic Class Selection (DCS) framework in the context of Proportional Delay Differentiation (PDD). We illustrate that, under certain conditions, DCS-capable users can meet absolute QoS requirements, even though the network only offers relative differentiation. For a simple link model, we give an algorithm that checks whether it is feasible to satisfy all users, and if this is the case, computes 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 and even unacceptable DCS equilibria may also exist. Simulations of an end-to-end DCS algorithm provide further insight in the dynamic behavior of DCS, show the relation between DCS and the network Delay Differentiation Parameters, and demonstrate how to control the trade-off between a flow's performance and cost using DCS.

Citations