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

• Published in: Electronics (Basel) Vol. 10; no. 8; p. 876
• Main Authors: Gonçalves, Igor, Rodrigues, Laécio, Silva, Francisco Airton, Nguyen, Tuan Anh, Min, Dugki, Lee, Jae-Woo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 07.04.2021
• Subjects: Automation; Availability; Business metrics; Cameras; Communication; Computer architecture; Crime prevention; Design of experiments; Internet of Things; Markov analysis; Mean time to failure; Monitoring; Monitoring systems; Performance evaluation; Petri nets; Proposals; Quality of service; Reliability analysis; Sensitivity analysis; Smart cities; Social problems; Stochastic models; Surveillance; System reliability; Trust; Video data; Wireless networks
• ISSN: 2079-9292; 2079-9292
• DOI: 10.3390/electronics10080876

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