A case for relative differentiated services and the proportional differentiation model

Internet applications and users have very diverse quality of service expectations, making the same-service-to-all model of the current Internet inadequate and limiting. There is a widespread consensus today that the Internet architecture has to extended with service differentiation mechanisms so that certain users and applications can get better service than others at a higher cost. One approach, referred to as absolute differentiated services, is based on sophisticated admission control and resource reservation mechanisms in order to provide guarantees or statistical assurances for absolute performance measures, such as a minimum service rate or maximum end-to-end delay. Another approach, which is simpler in terms of implementation, deployment, and network manageability, is to offer relative differentiated services between a small number of service classes. These classes are ordered based on their packet forwarding quality, in terms of per-hop metrics for the queuing delays and packet losses, giving the assurance that higher classes are better than lower classes. The applications and users, in this context, can dynamically select the class that best meets their quality and pricing constraints, without a priori guarantees for the actual performance level of each class. The relative differentiation approach can be further refined and quantified using the proportional differentiation model. This model aims to provide the network operator with the “tuning knobs” for adjusting the quality spacing between classes, independent of the class loads. When this spacing is feasible in short timescales, it can lead to predictable and controllable class differentiation, which ore two important features for any relative differentiation model. The proportional differentiation model can be approximated in practice with simple forwarding mechanisms (packet scheduling and buffer management) that we describe