MCRel: A Minimal Cut Set-Based Approach for Reliability Analysis of Sensor-Based IIoT

The rapid evolution of sensors has facilitated to its usage in the domain of Industrial IoT(IIoT). The component of IIoT includes sensors, devices, actuators, applications and cloud servers. Sensors are the important element of IIoT which are heavily prone to errors, interference and link issues etc. At this juncture, the efficiency and credibility of sensor networks has been a challenging problem for the design of IIoT system that can tolerate the network failure without any network disconnectedness, thereby improving the sustainability of the IIoT system for prolonged time period. Network reliability is a pivotal factor for finding the effectiveness of IIoT networks. This work proposes accurate and efficient minimal cut set based reliability estimation (MCRel) technique that analyzes the reliability of sensor networks and helps in well organized way of designing the IIoT system. This approach aims to estimate the reliability of the system using the self-generated minimal cut set based approach(MCRel). The algorithm is implemented on varied IIoT applications wavering from smaller to larger systems with complex communication links. This article presents an illustration of the generation of cut arcs and minimal cut sets, along with the framing of an unreliability expression with the computation of the reliability value. To evaluate the reliability of the IIoT system, a comprehensive analysis comparing MCRel with other contemporary algorithms has been conducted. The simulated findings demonstrate that, with an improvement of more than 15%, the MCRel outperforms competing algorithms, especially during the period of peak network traffic.