The evolution of fifth generation (5G) networks needs to support the latest use cases, which demand robust network connectivity for the collaborative performance of the network agents, like multi-robot systems and vehicle to anything (V2X) communication. Unfortunately, the user device's limited communication range and battery constraint confirm the unfitness of known robustness metrics suggested for fixed networks, when applied to time-switching communication graphs. Furthermore, the calculation of most of the existing robustness metrics involves non-deterministic polynomial-time complexity, and hence are best-fitted only for small networks. Despite a large volume of works, the complete analysis of a $\textit{low-complexity}$ temporal robustness metric for a communication network is absent in the literature, and the present work aims to fill this gap. More in detail, our work provides a stochastic analysis of network robustness for a massive machine type communication (mMTC) network. The numerical investigation corroborates the exactness of the proposed analytical framework for temporal robustness metric. Along with studying the impact on network robustness of various system parameters, such as cluster head (CH) probability, power threshold value, network size, and node failure probability, we justify the observed trend of numerical results probabilistically.
翻译:第五代(5G)网络的演进需要支持最新的使用案例,这些案例要求网络代理机构的合作性运行,如多机器人系统和任何(V2X)通信的车辆。不幸的是,用户装置的有限通信范围和电池限制证实,在应用时间转换通信图时,为固定网络建议的已知稳健度度度度度标准不适宜。此外,大多数现有稳健度度标准的计算涉及非确定性多元时间复杂性,因此只适合小型网络。尽管工作量很大,但文献中缺少对通信网络的美元/textit{low-complexity}($/textit{low-complility })的全面分析,目前的工作旨在填补这一空白。更详细地分析大规模机器类型通信网络的稳健性。数字调查证实了拟议的时间稳健度度度衡量分析框架的准确性。除了研究各种系统参数对网络稳健性的影响外,文献中缺少对通信网络时间稳健度度的完整度度度度度度度度度度度度度度指标,例如我们所观察到的概率、数字网络的概率阈值、所观察到的概率值(CH),我们所观察到的概率、数字网络的概率值、所观察到的概率模型的概率值。