Modelling BLUE Active Queue Management using Discrete-time Queue

This paper proposes a new discrete-time queue analytical model based on BLUE algorithm in order to determine the network congestion in preliminary stages. We compare the original BLUE, which has been implemented in Java, with our proposed analytical model with regards to different performance measures (average queue length, throughput, average queueing delay and packet loss probability). The comparison results show that the proposed discrete-time queue analytical model outperforms BLUE algorithm in terms of throughput and packet loss probability. Moreover, the proposed model maintains the throughput performance regardless whether the amount of the traffic load is light or heavy. Furthermore, we calculate the packet dropping probability function for our analytical model and the BLUE algorithm in order to decide which algorithm drops fewer packets.