With the success of wireless sensor networks (WSNs), traditional engineering and infrastructure industries are starting to develop solutions using WSN technologies. One of the main challenges of designing and developing WSNs for industrial monitoring and control is satisfying their strict reliability requirements. In this paper, we present a network-level reliability model, namely, end-to-end data delivery reliability (E2E-DDR), for estimating and optimizing the reliability performance of WSNs. In the E2E-DDR model, a framework is presented for capturing the mapping function between the packet reception ratio, background noise, and received signal strength (RSS). We use an alpha-stable distribution to accurately represent the background noise and a modified log-normal path loss model to more realistically describe the RSS. We also report a comprehensive performance evaluation performed by applying the E2E-DDR model in a real-world case study to estimate the network-level reliability and optimize the WSN deployment parameters.

中文翻译：

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用于估计和优化工业 WSN 链路质量的端到端数据传输可靠性模型


随着无线传感器网络 (WSN) 的成功，传统工程和基础设施行业开始使用 WSN 技术开发解决方案。设计和开发用于工业监测和控制的无线传感器网络的主要挑战之一是满足其严格的可靠性要求。在本文中，我们提出了一种网络级可靠性模型，即端到端数据传输可靠性（E2E-DDR），用于估计和优化无线传感器网络的可靠性性能。在E2E-DDR模型中，提出了一个框架来捕获数据包接收率、背景噪声和接收信号强度（RSS）之间的映射函数。我们使用 alpha 稳定分布来准确表示背景噪声，并使用修改后的对数正态路径损耗模型来更真实地描述 RSS。我们还报告了通过在实际案例研究中应用 E2E-DDR 模型来评估网络级可靠性并优化 WSN 部署参数而进行的全面性能评估。