Derivation of Three Queue Nodes Discrete-Time Analytical Model Based on DRED Algorithm

Abstract

This paper proposes a derivation of discrete-time queuing network analytical model based on dynamic random early drop (DRED) algorithm to manage and control congestion in early stages before it occurs, which is referred to as the 3QN model. The proposed model consists of three interconnected queue processing nodes. Expressions were derived to calculate performance measures, namely; throughput, and average queuing delay. In order to investigate and analyze the effectiveness and flexibility of the proposed model, two scenarios were performed. These scenarios investigate the variation of packets arrival probability against throughput), and average queuing delay. Beside that we compare between the three queue nodes of the proposed model using the derived performance measures to identify which queue node provides better performance. Results show that queue node one has better performance than queue node two and three with regard to throughput. All the above performance measure results for the queue nodes are obtained only based on the queuing network setting parameters. Therefore the node which offers better performance results than others is solely based on the given values for the setting parameter.