Integrated Random Early Detection for Congestion Control at the Router Buffer

This paper proposed an Integrated Random Early Detection(IRED)method that aims to resolve the problems of the queue-based AQM and loadbased AQM and gain the benefits of both using indicators from both types.The arrival factor(e.g.,arrival rate,queue and capacity)and the departure factors are used to estimate the congestion through two integrated indicators.The utilized indicators are mathematically calculated and integrated to gain unified and coherent congestion indicators.Besides,IRED is built based on a new dropping calculation approach that fits the utilized congestion indicators while maintaining the intended buffer management criteria,avoiding global synchronization and enhancing the performance.The results showed that IRED,compared to RED,BLUE,ERED,FLRED,EnRED and DcRED,decreased packet delay and loss under various network status.Specifically,the results showed that in heavy and moderate traffic,the proposed IRED method outperformed the state-of-the-art methods in loss and delay by 18% and 10.6%,respectively.

BIFURCATIONS AND CHAOS CONTROL IN TCP-RED SYSTEM

Objective Analyzing the nonlinear dynamics of the TCP-RED congestion control system is of great importance. This study will help investigate the loss of stability in Internet and design a proper method for controlling bifurcation and chaos in such system. Methods Based on bifurcation diagram, the effect of parameter on system performance is discussed. By using the state feedback and parameter variation strategy, a simple real time control method is proposed to modify the existing RED scheme. Results With our control method, the parametric sensitivity of RED mechanism is attenuated. Moreover, a sufficient condition on the robust stability of the system is also derived to adjust the parameters in TCP-RED system. Conclusion The proposed method has the advantages of simple implementation and unnecessary knowledge of the exact system.

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Congestion control is one of the main obstacles in cyberspace traffic.Overcrowding in internet traffic may cause several problems;such as high packet hold-up,high packet dropping,and low packet output.In the course of data transmission for various applications in the Internet of things,such problems are usually generated relative to the input.To tackle such problems,this paper presents an analytical model using an optimized Random Early Detection(RED)algorithm-based approach for internet traffic management.The validity of the proposed model is checked through extensive simulation-based experiments.An analysis is observed for different functions on internet traffic.Four performance metrics are taken into consideration,namely,the possibility of packet loss,throughput,mean queue length and mean queue delay.Three sets of experiments are observed with varying simulation results.The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.