IGRED: An Improved Gentle Random Early Detection Method for Management of Congested Networks

Abstract

Controlling congested router buffers of a network has a crucial role in improving network’s performance. This paper proposes a novel Active Queue Management (AQM) method named Improved Gentle Random Early Detection (IGRED) that based on GRED algorithm, which counted as one of the popular AQM methods. The proposed is mainly developed to overcome the problems faced with classic GRED. The initial packet-dropping probability depends on several parameters such as the average queue length, maximum value of packet dropping probability, minimum and maximum thresholds, etc. IGRED reduces its reliance on the GRED’s parameters through shrinking these parameters. The results shows, when congestion is taken place, the proposed IGRED provides more satisfactory performance with reference to mean queue length, average queuing delay, and overflow packet loss probability.