## 1 Introduction
The study revealed that the overall reliability of a WSN is affected by routing protocol, density of nodes, and distance between nodes [16]. [PERSON] et al. [17] highlighted the impact of redundancy and node deployment on the reliability of WSNs in smart farming by comparing series RBD and territory-based FTA, which signify that hybrid RBD is the most reliable model. [PERSON] and [PERSON] [18] introduced a Markov model for quantitatively analyzing the reliability of satellite communication networks that utilize onboard processing (OBP) satellites. The results showed that network reliability is significantly affected by both satellite channels and onboard processing (OBP) structures. Markov processes have been used to design a P2P network to evaluate different reliability characteristics for the same. The author also emphasizes the components whose failure rates have to be controlled in order to achieve high reliability for the P2P network [19]. [PERSON] et al. [20] studied IoT-based FAS to understand the nature of different performance measures; here, authors also performed sensitivity analysis for the same. [PERSON] et al. [21] studied a \((k,n,G)\) system, with warm standby redundancy and sudden server failure, and found the reliability measures of it. [PERSON] and [PERSON] [22] analyzed the communication system's reliability using the Markov mathematical model. The authors also concluded that communication channel failures affect the system's reliability the most. [PERSON] et al. [23] extensively investigated network reliability by focusing on the importance of the network components using measures like Birnbaum importance. The study contributes to the improvement of network performance, which is crucial for architects and engineers. [PERSON] et al. [24] introduced a continuous-time Bayesian network for analyzing the reliability of a dynamic wireless communication network. [PERSON] [25] conducted a reliability and sensitivity analysis of a computer lab. IOT applications are evolving rapidly, and there is a need to address the complexity of these systems. [PERSON] [26] proposed a survey on existing models,focusing on their shortcomings and the need for a reliable model to address the ongoing revolutionary transformation. [PERSON] and [PERSON] [27] examined an IOT-based sensor system that is used in smart garbage collection bins. Using the Markov mathematical model, they identified the most vulnerable sensors and proposed a preventative maintenance strategy. [PERSON] et al. [PERSON] et al. (2018) presented a behavior-driven reliability modeling method for a complex WSN-based smart system. The method's effectiveness was illustrated through a case study on smart homes. The reliability measures of a mobile communication system (MCS) are investigated by [PERSON] et al. [PERSON] et al. (2019). A numerical-based case study has been performed to showcase the model graphically, as MCS has become a crucial need worldwide. [PERSON] et al. [PERSON] et al. (2019) examined the sensitivity analysis of wireless sensor networks concerning infrastructure communication reliability. [PERSON] et al. [PERSON] et al. (2019) addressed the reliability of mobile wireless sensor networks with multiple state nodes. A Monte Carlo Markov chain simulation is proposed for evaluating coverage-oriented reliability. [PERSON] et al. [PERSON] et al. (2019) estimated the availability of a steam turbine power plant. The key challenges were also discussed in the study. In spite of substantial research in the field of wireless sensor networks, the mathematical modeling of a wireless sensor network through the interconnection of its different components and their cumulative as well as individual effects on overall performance has not been considered, which is necessary for more accurate and effective evaluation.