Performance Evaluation of the Proposed Enhanced Adaptive Gentle Random Early Detection Algorithm in Congestion Situations

Abstract

Congestion control methods are continuously linked with the rapid advances in Internet and network technology. Congestion generally occurs when the amount of packets arriving at the router buffer cannot be accommodated. This paper proposed an Enhanced Adaptive Gentle Random Early Detection (Enhanced AGRED) method based on Adaptive Gentle Random Early Detection (AGRED) method in order to detect the congestion in early stage before the router buffer overflows by enhancing the parameter setting of Queue Weight (Qw). The Enhanced AGRED is simulated and compared with the AGRED and Gentle Random Early Detection (GRED) methods. The simulation results for the proposed Enhanced AGRED, GRED and AGRED methods are carried out by varying the variable of packet arrival probability to create different congestion/non-congestion scenarios. During the congestion, the simulation results reveals that Enhanced AGRED offers marginally better performance results than GRED and AGRED, with regard to mean queue length, average queuing delay and packet loss probability due to overflow. Therefore, the results prove that Enhanced AGRED is an effective method in controlling congestion router buffers of networks. Whereby, improve networks performance