AQM Model to Estimate and Mitigate Congestion using Priority RED in WSN

Abstract

In Wireless Sensor Networks (WSNs), most of the issues including energy management, topology management, bandwidth estimation, packet loss calculation, etc are dealt. Only few works have paid attention on mitigating congestion while estimating delay and bandwidth for transmitting data packets in WSNs. Several works on queue management and congestion control have incorporated Soft Computing (SC) techniques to solve some of the problems in WSNs. In this paper, an Active Queue Management (AQM) model to estimate congestion using priority Random Early Detection (RED) to mitigate congestion is proposed. The proposed method integrates AQM model with fuzzy subsystem which controls the admission of packets into the network and the same is compared with several existing works and is simulated using the Matlab simulator. It is found that the results obtained outperforms the existing methods in terms of delay between intermediate nodes, end-toend delay, packet loss ratio, packet loss probability, queue size and energy consumption.