Intelligent Traffic Routing Algorithm for Wireless Sensor Networks in Agricultural Environment

Pub Date : 2023-01-01 DOI:10.12720/jait.14.1.46-55
T. M. Tshilongamulenzhe, Topside E. Mathonsi, D. D. Plessis, M. Mphahlele
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引用次数: 2

Abstract

Wireless Sensor Networks (WSNs) is an area that has attracted a lot of attention currently worldwide. WSNs are implemented to monitor temperature, humidity, and pressure, among others within the agricultural environment. This paper addresses the traffic congestion that occurs within WSNs in the agricultural environment during packet transmission that is normally caused by head-of-line blocking. As a result, packet loss, packet delay, and network performance impairment occurred during packet distribution in the network. This paper proposed an Intelligence Traffic Routing (ITR) algorithm to manage packet flow to avoid traffic congestion in WSNs within the agricultural environment while improving Quality of Service (QoS). The LBRM (Load Balancing Routing Management) and MLCC (Machine Learning Congestion Control) algorithms were integrated to develop the proposed ITR algorithm. Network Simulator 2 (NS-2) was used to test the effectiveness of the proposed ITR algorithm. The simulation results showed that the proposed ITR algorithm reduced packet loss by 27.3%, packet delay by 43.4%, and improved network throughput by 98.4% when compared with LBRM and MLCC algorithms.
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农业环境下无线传感器网络的智能交通路由算法
无线传感器网络(WSNs)是目前世界范围内备受关注的一个领域。实现wsn用于监测农业环境中的温度、湿度和压力等。本文研究了农业环境下无线传感器网络在分组传输过程中发生的流量拥塞问题,这种拥塞通常是由线头阻塞引起的。在网络中分发报文时,会出现丢包、报文延迟、网络性能降低等问题。本文提出了一种智能流量路由(ITR)算法,在提高服务质量(QoS)的同时,对农业环境下的无线传感器网络进行分组流管理,避免网络中的流量拥塞。将负载均衡路由管理(LBRM)和机器学习拥塞控制(MLCC)算法集成在一起,开发了提出的ITR算法。利用网络模拟器2 (NS-2)测试了所提出的ITR算法的有效性。仿真结果表明,与LBRM和MLCC算法相比,提出的ITR算法丢包率降低27.3%,时延降低43.4%,网络吞吐量提高98.4%。
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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