Effectively and fairly allocating resources to the competing users in a network is a major issue to meet the demand for higher performance nowadays. How to provide better congestion control for network emerges as a major issue. The problem of congestion control is reduced with the help of active queue management techniques. The main objective of this research is to simulate and analyze the effect of queuing algorithms such as DropTail, Fair Queuing (FQ), Stochastic Fair Queuing (SFQ), Deficit Round Robin (DRR) and Random Early Detection (RED) using ns-2 as a simulation environment. It is an approach in developing a comparison on congestion avoidance algorithms for router-based communication and conclude that Stochastic fair queuing give better performance among all and provides an effective way to insulate users from ill behaved sources and improve the drawback of the queuing algorithm. Stochastic Fair Queuing algorithm can give fair allocation of bandwidth to each source nodes and packet loss can be minimized and dropped packets can be retransmitted and network congestions can be managed in efficient way. The results also indicate that UDP type attack traffic is more powerful as compared to TCP type attack. The performance metrics of the comparison are average delay and packet drop and throughput The algorithms are tested in terms of delay , throughput fairness, utilization and packet loss rate by applying various number of flows under TCP, and TCP/UDP traffic.

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Queuing Algorithms Aqm Packet Drop Ns2