Drone Surveillance System Availability and Reliability: A Comprehensive Analytical and Numerical Modeling Approach

This paper proposes an approach to evaluate the availability and reliability of drone surveillance systems using complementary modeling techniques. Resilient system architecture with drone and battery redundancy is analyzed using two modeling strategies: (i) an analytical model based on Continuous-Time Markov Chains (CTMC), which yields closed-form availability equations, and (ii) a numerical model employing Stochastic Petri Nets (SPN) to handle more complex redundancy scenarios. Both models consider key factors such as battery charging/discharging times, drone failure and repair rates, and replacement operations. Sensitivity analyses highlight battery-related parameters as critical to system performance. Case studies show that optimizing component parameters can yield up to 97% availability, while redundancy alone can provide 91%. Combined strategies can achieve up to 99.89% availability. For long missions (30 hours), reliability analysis indicates that 15--20 redundant batteries and charging times below 36 minutes are needed to maintain over 80% reliability. For shorter missions, discharge times over 144 minutes are beneficial. This integrated modeling approach provides a robust framework for dependability assessment, guiding the design of resilient and cost-effective drone surveillance systems for mission-critical applications.