Abstract

Congestion control is necessary for enhancing the quality of service in wireless sensor networks (WSNs). With advances in sensing technology, a substantial amount of data traversing a WSN can easily cause congestion, especially given limited resources. As a consequence, network throughput decreases due to significant packet loss and increased delays. Moreover, congestion not only adversely affects the data traffic and transmission success rate but also excessively dissipates energy, which in turn reduces the sensor node and, hence, network lifespans. A typical congestion control strategy was designed to address congestion due to transient events. However, on many occasions, congestion was caused by repeated anomalies and, as a consequence, persisted for an extended period. This paper thus proposes a congestion control strategy that can eliminate both types of congestion. The study adopted a fuzzy logic algorithm for resolving congestion in three key areas: optimal path selection, traffic rate adjustment that incorporates a momentum indicator, and an optimal timeout setting for a circuit breaker to limit persistent congestion. With fuzzy logic, decisions can be made efficiently based on probabilistic weights derived from fitness functions of congestion-relevant parameters. The simulation and experimental results reported herein demonstrate that the proposed strategy outperforms state-of-the-art strategies in terms of the traffic rate, transmission delay, queue utilization, and energy efficiency.

中文翻译：

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使用断路器的模糊逻辑速率调整控制，用于无线传感器网络中的持续性拥塞

摘要

拥塞控制对于提高无线传感器网络（WSN）中的服务质量是必需的。随着传感技术的进步，遍历WSN的大量数据很容易引起拥塞，特别是在资源有限的情况下。结果，由于显着的分组丢失和增加的延迟，网络吞吐量降低。此外，拥塞不仅会对数据流量和传输成功率产生不利影响，而且还会过多地耗散能量，从而减少了传感器节点，从而缩短了网络寿命。设计了一种典型的拥塞控制策略来解决由于瞬态事件引起的拥塞。但是，在许多情况下，拥塞是由反复的异常引起的，因此持续了很长时间。因此，本文提出了一种可以同时消除两种类型的拥塞的拥塞控制策略。这项研究采用了模糊逻辑算法来解决三个关键领域的拥堵：最佳路径选择，结合了动量指标的流量调整以及用于限制持续拥堵的断路器的最佳超时设置。利用模糊逻辑，可以基于从与拥塞相关的参数的适应度函数得出的概率权重，高效地做出决策。本文报道的仿真和实验结果表明，在流量速率，传输延迟，队列利用率和能源效率方面，所提出的策略优于最新策略。最佳路径选择，结合了动量指示器的流量调节以及断路器的最佳超时设置以限制持续的拥塞。利用模糊逻辑，可以基于从与拥塞相关的参数的适应度函数得出的概率权重，高效地做出决策。本文报道的仿真和实验结果表明，在流量速率，传输延迟，队列利用率和能源效率方面，所提出的策略优于最新策略。最佳路径选择，结合了动量指示器的流量调节以及断路器的最佳超时设置以限制持续的拥塞。利用模糊逻辑，可以基于从与拥塞相关的参数的适应度函数得出的概率权重，高效地做出决策。本文报道的仿真和实验结果表明，在流量速率，传输延迟，队列利用率和能源效率方面，所提出的策略优于最新策略。