Intelligent traffic management algorithm for wireless sensor networks

Abstract

Wireless Sensor Networks (WSNs) are used to simplify various real-time applications which include traffic management, humidity, monitoring of the temperature, and pressure by using a wide range of sensor nodes. Sensor nodes are assigned through various resource restrictions such as allocated bandwidth, available memory, and battery power. This research paper demonstrated the packet congestion issue that happens during packet distribution from the source node to destination node. The packet congestion in WSNs is normally caused by Buffer overflow. This leads to the decrement of network throughput, packet drop, and high end-to-end delay during packet transmission from and to different nodes. Therefore, in order to avoid packet congestion in WSNs, an Intelligent Traffic Management (ITM) algorithm is proposed. The proposed ITM algorithm was developed by integrating different algorithms namely: Modified Neural Network Wavelet Congestion Control (MNNWCC) algorithm and Tree-based Congestion Control (TACC) algorithm. The simulation is performed using the Network Simulator 2 (NS-2) simulation platform. The simulation results showed that the proposed ITM algorithm improves the network throughput by 97.1 %, reduce packet drop by 32%, and end-to-end delay minimized by 27% when compared with MNNWCC algorithm and TACC algorithm.