Processing rate allocation for proportional slowdown differentiation on Internet servers

Summary form only given. A proportional differentiation model states that quality of service of different classes of Internet traffic should be kept proportional to their prespecified differentiation parameters, independent of the class loads. The model has been applied in the proportional queueing delay differentiation (FDD) in both network core and network edges. However, in the server side, an important and interesting performance metric is slowdown, the ratio of a request´s queueing delay to its service time. Slowdown is important because it is desirable that a request´s delay be proportional to its processing requirement. We investigate the problem of processing rate allocation for proportional slowdown differentiation (PSD) on Internet servers. Existing algorithms for FDD provisioning in the network side are not applicable to PSD provisioning in the server side because slowdown is not only dependent on a job´s queueing delay but also on its service time, which varies significantly depending on the requested services. We first derive a closed form expression of the expected slowdown in an M/Gp/1 FCFS queue, which is an M/G/l FCFS queue with a typical heavy-tailed service time distribution (bounded Pareto distribution). PSD provisioning is realized by deploying a task server for handling each request class in a FCFS way. We then develop a strategy of processing rate allocation for the task servers for PSD provisioning. Simulation results have showed that the proposed rate allocation strategy can provide predictable and controllable PSD services on the servers.