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Performance evaluation of fuzzy logic-based congestion optimisation approach for sensor networks

机译:基于模糊逻辑的传感器网络拥塞优化方法的性能评估

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摘要

Congestion in WSN leads to excessive consumption of energy, which needs to be controlled to improve the system life time. Congestion estimation has always been an important issue in wireless sensor networks for efficient information processing. In the recent past some researchers have used fuzzy logic for congestion estimation and shown that fuzzy logic is a potential tool for detection and estimation of congestion in wireless sensor networks. In this work we have used four different fuzzy systems for congestion estimation and evaluated their performances. Through these four fuzzy systems we will estimate the number of dropped packets with respect to time. In addition to this we have also found the average number of packet dropped for time interval 0 to 100 seconds, with respect to number of nodes in a certain cluster. Three important parameters affecting information processing and congestion in wireless sensor networks are identified as packet forwarding ratio, delay and validity. Simulation results of these fuzzy systems show that validity and delay-based system gives best performance and minimises packet drops to a significant amount during information processing in wireless sensor networks.
机译:WSN中的拥塞导致过多的能量消耗,需要对其进行控制以改善系统寿命。对于有效的信息处理,拥塞估计一直是无线传感器网络中的重要问题。在最近的过去,一些研究人员已经使用模糊逻辑进行拥塞估计,并表明模糊逻辑是用于检测和估计无线传感器网络中拥塞的潜在工具。在这项工作中,我们使用了四个不同的模糊系统进行拥塞估计并评估了它们的性能。通过这四个模糊系统,我们将估计相对于时间的丢包数量。除此之外,我们还发现,相对于特定集群中的节点数,在0到100秒的时间间隔内丢弃的平均数据包数。确定了影响无线传感器网络中信息处理和拥塞的三个重要参数,即数据包转发率,延迟和有效性。这些模糊系统的仿真结果表明,在无线传感器网络的信息处理过程中,基于有效性和时延的系统可提供最佳性能,并将丢包率降至最低。

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