Control of Congestion Effects in Wireless Sensor Network with Mobile Sink Node Based on Wavelet Neural Network

Nadia Adnan Shiltagh Al-Jamali; Nariman Riyadh Mohammed Ali Al-Tahan

Nadia Adnan Shiltagh Al-Jamali Asst. Prof.-University of Baghdad /Computer Engineering Baghdad, Iraq
Nariman Riyadh Mohammed Ali Al-Tahan University of Baghdad /Computer Engineering Baghdad, Iraq

Keywords: Wireless Sensor Network, mobile sink node, congestion control

Abstract

In this paper, the Wireless Sensor Network with random mobility sink node is introduced in order to improve the Quality of Service (QoS) based on intelligent controller. This controller is designed based on (Wavelet-Neural Network). The clustering technique is used in the WSN, to enhance the routing algorithm. To quantify the level of performance of the algorithm proposed in this paper, Network Simulator (NS-2) is used which is installed on Ubuntu 14.04. Simulation results show that the proposed algorithm can effectively reduce congestion and enhance the QoS by achieve better throughput, better packet delivery ratio, less End-To-End delay and Packet-loss. The Comparison of the performance of the network with No Congestion Controller (NCC), Neural Network Congestion Controller (NNCC) and Wavelet Neural Network Congestion Controller (WNNCC) is introduced. It is found that the performance with WNNCC is better than performance with NCC and NNCC. The study of the WNNCC and NNCC is done. The resultant average throughput, End-To-End Delay, count receive packet, count Packet-Loss, and Packet Delivery Ratio are compared between WNNCC and NNCC. The simulation of BP algorithm is performed using MATLAB R2014a software running the computer with the following specifications: windows 7 (32-bit), core i5, RAM 4 GB.