DYNAMIC STOCHASTIC EARLY DISCOVERY: A NEW CONGESTION CONTROL TECHNIQUE TO IMPROVE NETWORKS PERFORMANCE

Abstract

The present paper proposes the Dynamic Gentle Random Early Detection (DGRED) algorithm for early stage congestion detection at the router buffer. Generally, the proposed DGRED algorithm depends on the stability of the average queue length at a specic level between allocated minimum and maximum threshold values, with the aim to improve the network performance. The DGRED algorithm is simulated and compared with the most known Active Queue Management Early Detection (RED) algorithm and two of its variants, namely, Gentle RED and Adaptive GRED. This comparison was con- ducted based on different performance measures, such as mean queue length, throughput, average queuing delay, packet loss, and dropping probability for packets. The comparison aimed to identify the algorithm that offers better performance measurement results under either non-congestion or congestion situation at the router buffers. The acquired results show that the proposed algorithm contributes in providing lesser queue length, delayed queuing, and packet loss probability compared with the existing algorithms when high packet arrival probability appears, that is, ( > 0 :63) . Furthermore, DGRED generates