Two Different Approaches of Active Queue Management

With the rapid growth of computer networks, particularly in the Internet, the control of congestion has become one of the most critical issues in present networks to accommodate the increasingly diverse range of services and types of traffic. The Internet growth requires expansion of congestion control to network routers which can be achieved by satisfying the specified quality of service (QoS) constraints. In this paper we present two new approaches for congestion control based on random early detection (RED) using queue thresholds. The two proposed models dynamically adjust maximum dropping probability and maximum threshold with the aim of stabilizing the mean queue size and satisfying specified quality of service constraints such as Bandwidth and delay. The performance results for the two models show good results in terms of stabilizing the mean queue length, delay and packet loss. The maximum dropping probability approach has successfully produced low variation of the mean queue length.