Congestion detection in Wireless sensor network using neural network

Prakul Singhal, Anamika Yadav
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引用次数: 15

Abstract

In Wireless sensor network (WSN), sink nodes are bottleneck of network due to congestion. Congestion deteriorates the overall performance of the system. So congestion detection in a WSN is very vital issue in the present scenario. In this paper, artificial neural network based congestion detection algorithm is developed. The neural network based congestion detection system uses number of participants, buffer occupancy, and traffic rate as input parameters and gives the congestion level as output. A number of NS-2 and MATLAB simulation results show that the proposed scheme accurately detects the congestion level and represents the state of congestion in the WSN.
基于神经网络的无线传感器网络拥塞检测
在无线传感器网络(WSN)中,由于网络拥塞,汇聚节点成为网络的瓶颈。拥塞会影响系统的整体性能。因此,在无线传感器网络中进行拥塞检测是一个非常重要的问题。本文提出了一种基于人工神经网络的拥塞检测算法。基于神经网络的拥塞检测系统以参与者数量、缓冲区占用率和流量率作为输入参数,并给出拥塞程度作为输出。大量的NS-2和MATLAB仿真结果表明,该方案能够准确地检测到WSN的拥塞程度,并表示WSN的拥塞状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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