Wireless sensor networks (WSNs) form a large part of the ecosystem of the Internet of Things (IoT), hence they have numerous application domains with varying performance and availability requirements. Limited resources that include processing capability, queue capacity, and available energy in addition to frequent node and link failures degrade the performance and availability of these networks. In an attempt to efficiently utilise the limited resources and to maintain the reliable network with efficient data transmission; it is common to select a clustering approach, where a cluster head is selected among the diverse IoT devices. This study presents the stochastic performance as well as the energy evaluation model for WSNs that have both node and link failures. The model developed considers an integrated performance and availability approach. Various duty cycling schemes within the medium-access control of the WSNs are also considered to incorporate the impact of sleeping/idle states that are presented using analytical modeling. The results presented using the proposed analytical models show the effects of factors such as failures, various queue capacities and system scalability. The analytical results presented are in very good agreement with simulation results and also present an important fact that the proposed models are very useful for identification of thresholds between WSN system characteristics.

中文翻译：

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集群物联网系统的性能、可用​​性和能耗建模

无线传感器网络 (WSN) 构成了物联网 (IoT) 生态系统的很大一部分，因此它们具有众多具有不同性能和可用性要求的应用领域。除了频繁的节点和链路故障之外，包括处理能力、队列容量和可用能量在内的有限资源会降低这些网络的性能和可用性。试图有效地利用有限的资源并通过高效的数据传输来维护可靠的网络；通常选择一种聚类方法，在不同的物联网设备中选择一个簇头。本研究提出了具有节点和链路故障的 WSN 的随机性能以及能量评估模型。开发的模型考虑了集成的性能和可用性方法。WSN 的媒体访问控制中的各种工作循环方案也被考虑纳入使用分析建模呈现的睡眠/空闲状态的影响。使用建议的分析模型呈现的结果显示了诸如故障、各种队列容量和系统可扩展性等因素的影响。所呈现的分析结果与仿真结果非常吻合，并且还提出了一个重要事实，即所提出的模型对于识别 WSN 系统特征之间的阈值非常有用。使用建议的分析模型呈现的结果显示了诸如故障、各种队列容量和系统可扩展性等因素的影响。所呈现的分析结果与仿真结果非常吻合，并且还提出了一个重要事实，即所提出的模型对于识别 WSN 系统特征之间的阈值非常有用。使用建议的分析模型呈现的结果显示了诸如故障、各种队列容量和系统可扩展性等因素的影响。所呈现的分析结果与仿真结果非常吻合，并且还提出了一个重要事实，即所提出的模型对于识别 WSN 系统特征之间的阈值非常有用。