The reliability of wireless Ad Hoc Networks (WANET) communication is much lower than wired networks. WANET will be impacted by node overload, routing protocol, weather, obstacle blockage, and many other factors, all those anomalies cannot be avoided. Accurate prediction of the network entirely stopping in advance is essential after people could do networking re-routing or changing to different bands. In the present study, there are two primary goals. Firstly, design anomaly events detection patterns based on Metamorphic Testing (MT) methodology. Secondly, compare the performance of evaluation metrics, such as Transfer Rate, Occupancy rate, and the Number of packets received. Compared to other studies, the most significant advantage of mathematical interpretability, as well as not requiring dependence on physical environmental information, only relies on the networking physical layer and Mac layer data. The analysis of the results demonstrates that the proposed MT detection method is helpful for automatically identifying incidents/accident events on WANET. The physical layer transfer Rate metric could get the best performance.

翻译：无线自组织网络（WANET）的通信可靠性远低于有线网络。WANET会受到节点过载、路由协议、天气、障碍物遮挡等多种因素的影响，这些异常均难以避免。准确预测网络完全中断的时间对于提前进行网络重路由或切换频段至关重要。本研究主要包含两个目标：其一，基于蜕变测试（MT）方法设计异常事件检测模式；其二，对比评估指标（如传输速率、信道占用率、接收数据包数量）的性能表现。与其他研究相比，本方法最显著的优势在于其数学可解释性，且无需依赖物理环境信息，仅需使用网络物理层和MAC层数据。分析结果表明，所提出的MT检测方法有助于自动识别WANET中的异常事件。其中物理层传输速率指标可获得最佳检测性能。