Dynamic-CBT:
Better Performing Active Queue Management
for Multimedia Networking
Jae Chung & Mark Claypool
Worcester Polytechnic Institute
Abstract:
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 Class-Based
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.