Modeling and Evaluation of Dependability in Robotic Telesurgery with Distance-Aware Supervised Failover

Abstract Robotic telesurgery requires reliable and continuous communication between the surgeon’s console and the surgical robot. Although prior studies have examined network performance and latency, few have developed analytical models that capture how communication failures and recovery mechanisms influence system dependability, which limits the ability to anticipate risks and design resilient infrastructures. This work proposes a dependability modeling approach for robotic telesurgery, called the dependability modeling for robotic telesurgery, which integrates the main stages of the operational flow and incorporates two key elements, namely the explicit modeling of geographical distance, affecting propagation delay and message delivery probability, and a supervised failover mechanism activated after failure detection and validation. Using Stochastic Petri Nets as the underlying analytical modeling technique, the study evaluates important dependability metrics such as availability, reliability, message delivery probability, round trip time and failover time. Experimental results show how the proposed approach assesses the impact of distance and supervised failover on system behavior, revealing their effects on operational continuity and communication efficiency and providing quantitative support for the design of more reliable and predictable telesurgery infrastructures.