A dynamic DRR scheduling algorithm for flow level QOS assurances for elastic traffic

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Bilkent University
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Best effort service, used to transport the Internet traffic today, does not provide any 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 traffic are prioritized, while elastic flows share the remaining bandwidth. As opposed to the well studied differential treatment of delay and/or loss sensitive traffic to satisfy QoS constraints, our aim is satisfy QoS requirements of elastic traffic at the flow level. We intend to maintain different average rate levels for different classes of elastic traffic. For differential treatment of elastic flows, a dynamic variant 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 in proportion to their weights at each round. The main difference of our scheduler from the original DRR scheduler is that, we update the weights, which are called quantums of the scheduler at each round in response to the feedback from the network, which is in terms of the rate of phantom connection sharing capacity fairly with the other flows in the same queue. According to the rate measured in the last time interval, the controller updates the weights in proportion with the bandwidth requirements of each class to satisfy their QoS requirements, while the remaining bandwidth will be used by the best effort traffic. In order to find an optimal policy for the controller a simulation-based learning algorithm is performed using a processor sharing model of TCP, then the resultant policies are applied to a more realistic scenario to solve Dynamic DRR scheduling problem through ns-2 simulations.

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Dynamic Deficit Round Robin Scheduling, Reinforcement Learning, QoS, Elastic Traffic
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