Delay differentiation and adaptation in core stateless networks

We present a core-stateless quality of service architecture for achieving delay differentiation between flows. There are two key components in our approach: (1) per-class per-hop relative average delay-the average queueing delay perceived by the packets in a delay class at a link is inversely proportional to the delay weight of the class; (2) per-flow end-to-end delay class adaptation-the delay class of a flow is dynamically adjusted based on its perceived end-to-end delay in order to maintain the desired end-to-end average delay requirement of the flow. We show through simulations and analysis that these two components can, in concert, support end-to-end delay differentiation between flows using only simple mechanisms at the core routers in the network.