Esnek trafik için akış seviyesinde dinamik çizelgeleme algoritması

Best effort service, used to transport the Internet traffic today, does not provideany QoS assurances. Intserv, DiffServ and recently proposed Proportional Diff-Serv architectures have been introduced to provide QoS. In these architectures,some applications with more stringent QoS requirement such as real time trafficare prioritized, while elastic flows share the remaining bandwidth. As opposedto the well studied differential treatment of delay and/or loss sensitive traffic tosatisfy QoS constraints, our aim is satisfy QoS requirements of elastic traffic atthe flow level. We intend to maintain different average rate levels for differentclasses of elastic traffic. For differential treatment of elastic flows, a dynamic vari-ant of Deficit Round Robin Scheduler (DRR) is used as oppose to a FIFO queue.In this scheduling algorithm, all classes are served in a round robin fashion inproportion to their weights at each round. The main difference of our schedulerfrom the original DRR scheduler is that, we update the weights, which are calledquantums of the scheduler at each round in response to the feedback from thenetwork, which is in terms of the rate of phantom connection sharing capacityfairly with the other flows in the same queue. According to the rate measured iniiithe last time interval, the controller updates the weights in proportion with thebandwidth requirements of each class to satisfy their QoS requirements, whilethe remaining bandwidth will be used by the best effort traffic. In order to findan optimal policy for the controller a simulation-based learning algorithm is per-formed using a processor sharing model of TCP, then the resultant policies areapplied to a more realistic scenario to solve Dynamic DRR scheduling problemthrough ns-2 simulations.Keywords: Dynamic Deficit Round Robin Scheduling, Reinforcement Learning,QoS, Elastic Trafficiv