Dynamic-CBT – Better Performing Active Queue Management for Multimedia Networking

The explosive increase in the volume and variety of Internet traffic has placed a growing emphasis on congestion control and fairness in Internet routers. Approaches to the problem of congestion, such as active queue management schemes like Random Early Detection (RED) use congestion avoidance techniques and are successful with TCP flows. Approaches to the problem of fairness, such as Fair Random Early Drop (FRED), punish misbehaved, non-TCP flows. Unfortunately, these punishment mechanisms also result in a significant performance drop for multimedia flows that use flow control and do not scale since they require per-flow state information. We extend ClassBased Threshold (CBT) [4], and propose a new active queue management mechanism as an extension to RED called Dynamic Class-Based Threshold (D-CBT) to improve multimedia performance on the Internet. The performance of our proposed mechanisms is measured, analyzed and compared with other mechanisms (RED and CBT) in terms of throughput and fairness through simulation using NS. The study shows that D-CBT improves fairness among different classes of flows.