Red Queue's Occupancy And Performance

Abstract

Random Early Detection (RED) is a queue management algorithm used in packet routers of Internet Protocol (IP) networks. It drops/marks packets with a certain probability before packet buffers overflow with the aim of improving TCP performance. RED and other queue management algorithms that drop packets early to adjust network traffic are classified as Active Queue Management (AQM). This contrasts with traditional queue management that drops packets only when packet buffers overflow. The RED algorithm is composed of three parts: a queue size averaging mechanism, a drop probability function, and a dropping algorithm. When a packet arrives at a RED queue, RED decides to enqueue or drop/mark the packet using the three parts in its computation. In this thesis, we survey current AQM algorithms and discuss their strengths and limitations. We thoroughly investigate RED queue's occupancy and performance by testing the three parts of its algorithm separately. We derive an upper bound on RED's required buffering and investigate the effect of the queue size averaging mechanism on RED's performance through simulations. We define an extended RED model used to test the parameters of the drop probability function that affect the model's performance through simulations. Based on the simulation results, an improved AQM drop probability function is proposed. We also propose two dropping algorithms that decide how a packet is dropped. One of these two algorithms shows improvement over the original dropping algorithm of RED in the simulations.