A Dissertation Proposal on A Scalable Service Architecture for Quantitative Differentiation

Since its creation in the early seventies, the Internet has adopted a “best-effort” service, which relies on the following three principles: (1) No traffic is denied admission to the network, (2) all traffic is treated in the same manner, and (3) the only guarantee given by the network is that traffic will be transmitted in the best possible manner given the available resources, that is, no artificial delays will be generated, and no unnecessary losses will occur. The best-effort service is adequate as long as the applications using the network are not sensitive to variations in losses and delays (e.g., electronic mail), the load on the network is small and if pricing by network providers is not service-based. These conditions held in the early days of the Internet, when the Internet only consisted of network connections between a handful of universities. However, since the late eighties, these conditions do not hold anymore, for two main reasons. Firstly, an increasing number of different applications, such as real-time video [34], peer-to-peer networking (e.g., napster [4]), or the World-Wide Web [7], to name a few, have been using the Internet. These different applications have different needs in the service they must receive from the network. Secondly, the Internet has switched from a government-supported research network to a commercial entity in 1994, thereby creating a need for service-based pricing schemes that can better recover cost and maximize revenue than a best-effort network. These two factors have created a demand for different levels of service. In some ways, the Internet has been victim of its success, and finding a solution to the problem of providing different levels of services in the network became critical to ensure the survival of the Internet. The issues for providing different levels of services in the network are referred to as providing Quality-of-Service (QoS) guarantees. One could think that QoS issues can be resolved by increasing the capacity of the network. This solution faces two major problems. First, the QoS received by an end-to-end traffic flow is bounded by the QoS received at the link with the smallest capacity (i.e., bottleneck) on the end-to-end path. Thus, augmenting the capacity of some links only moves the bottleneck to another part of the network, and consequently, only changes the location of the problem. Second, the capacity of the network links of the Internet has steadily increased in the past couple of years and only resulted in an increase of the traffic that uses these links, without providing any QoS. In fact, the recent explosion of link capacity in the network, instead of solving the problem of providing service guarantees, has put more stringent requirements on QoS architectures. Routers in the core of a packet network now have to serve millions of concurrent flows at gigabit per second rates, which induces two scalability requirements. First, the state information kept in the core routers for providing QoS should be small. Second, the processing time for classifying and scheduling packets according to their QoS guarantees should be small as well. In addition to these two scalability requirements, the fact the Internet is now mostly a commercial network requires to utilize the existing network resources as efficiently as possible, for instance, maximizing the utilization of the links. A number of service architectures for packet networks have been devised in the last decade in an effort to address these scalability and utilization requirements.