Identification and Minimization of Potential System Failures and Delays in Biometric Systems Using Queuing Theory

Abstract

This study investigates the identification and minimization of potential system failures and delays in biometric authentication systems through comprehensive queuing theory analysis and predictive modeling. The research employs advanced mathematical frameworks including M/M/1/C models, failure analysis techniques, and delay prediction algorithms to proactively identify bottlenecks and system vulnerabilities. Through simulation-based approaches and real-world case studies, this study develops systematic methodologies for predicting, preventing, and mitigating system failures while minimizing authentication delays. The findings provide actionable strategies for enhancing biometric system reliability and user experience through proactive failure management and delay optimization.