Congestion Control Approach based on Effective Random Early Detection and Fuzzy Logic

TL;DR

This paper introduces an improved congestion control method that extends ERED by incorporating delay considerations and fuzzy logic to optimize parameter settings, resulting in better network performance in delay and packet loss.

Contribution

It proposes an extended ERED method combined with fuzzy inference to address delay and parameter tuning issues in congestion control.

Findings

Enhanced packet loss reduction by 10-100%.

Delay improved by 30-60%.

Fuzzy-based method outperforms traditional ERED.

Abstract

Congestion in router buffer increases the delay and packet loss. Active Queue Management (AQM) methods are able to detect congestion in early stage and control it by packet dropping. Effective Random Early Detection (ERED) method, among many other AQM methods, gives a good performance in detect and control congestion and preserve packet loss. However, the ERED neglect the delay factor, which is effect the performance of the network. Moreover, ERED has a real parameterization problem. Several parameters have to be initialized to optimal values to obtain satisfactory results. This paper proposed an extended ERED method that considers the delay in its process and combines the extended ERED method with a Fuzzy Inference Process that eases the problem of parameter initialization. The results show that the parametric-based form of the proposed work gives a better performance results, according to the performance measures, delay, dropping and packet loss. The loss has been enhanced by 10-100%. Delay has been enhanced by 30-60%. The performance of the fuzzy-based form of the proposed method is better than the parametric-based form and ERED in terms of delay and packet loss.