Surveillance System in Smart Cities: A Dependability Evaluation Based on Stochastic Models

Surveillance monitoring systems are highly necessary, aiming to prevent many social problems in smart cities. The internet of things (IoT) nowadays offers a variety technologies capture and process massive heterogeneous data. Due the fact that (i) advanced analyses video streams performed on powerful recording devices; while (ii) surveillance services require high availability levels way service must remain connected, for example, connection network higher speed than conventional connections; (iii) trust-worthy dependability system depends various factors, it is not easy identify which components/devices architecture have most impact specific In this paper, we developed stochastic Petri net models with regard varying several parameters obtain highest dependability. Two main metrics interest including reliability were analyzed comprehensive manner. analysis results show variation number long-term evolution (LTE)-based stations contributes nines (#9s) increase availability. obtained mean time failure (MTTF) cameras exposes system. findings work potential assisting architects planning more optimized field based proposed models.