Random Early Detection Algorithm of Self-similar Traffic

A random early detection(RED) algorithm of self-similar traffic with self-similar traffic input can improve the effectiveness of network congestion control by taking the characteristic of traffic into account.Setting of parameters for the RED algorithm was investigated.Based on the characteristic of self-similar traffic,a parameter setting scheme for the RED algorithm of self-similar traffic was proposed,and the structure and implementation process of this algorithm were given.Based on fractional Brownian motion(FBM) and its envelope process,formulas of calculating the upper queue threshold and the packet drop rate in the RED algorithm were derived.The simulation results indicate that the proposed RED algorithm can well control the queue size and improve the performance of active queue management.Compared with the standard RED algorithm,the proposed RED algorithm can admit more connections under the condition of the same packet loss probability.