Importance-Based Reliability Allocation Using a Minimum-Effort Improvement Strategy for Complex Networks

Abstract

This study explains how to apply a minimum-effort improvement technique to provide reliability to intricate networks based on their importance. The study focuses on how crucial reliability is for identifying key components and determining the best way to distribute reliability throughout a system. We consider a sophisticated network with 10 components, and assume that all components are equally reliable at the start. First, the reliability of each part is calculated, and then the parts are sorted into groups based on their importance. The proposed method makes the system more reliable by equalizing the relevance of parts at different levels and adjusting their dependability values to match. Several instances of enhancement are examined to identify potential remedies within the reliability interval. The results show that improving some elements based on their actual importance does make the whole system work better. The final step in improving things is to adjust the reliability values for the four essential sections. This boosts the system's reliability from 0.6055 to 0.94. The recommended heuristic method is a simple yet effective strategy to make systems more reliable and spread reliability across complex networks