Dependability analysis and disaster recovery measures in smart hospital systems

There is a growing importance of the Internet of Medical Things (IoMT), an emerging aspect of the Internet of Things (IoT), in smart healthcare. With the emergence of the Coronavirus (COVID-19) pandemic, healthcare systems faced extreme pressure, leading to the need for advancements and research focused on IoMT. Smart hospital infrastructures face challenges regarding availability and reliability measures, especially in the event of local server failures or disasters. Unpredictable malfunctions in any aspect of medical computing infrastructure, from the power system in a remote area to local computing systems in a smart hospital, can result in critical failures in medical monitoring services. These failures can have serious consequences, including potentially fatal loss of life in the most serious cases. Therefore, we propose a disaster analysis and recovery measures using Stochastic Petri Nets (SPN) to resolve these critical issues. The proposed model aims to identify the system’s most critical components, develop strategies to mitigate failures and ensure system resilience. Our results show that the disaster recovery system demonstrated availability and reliability. The sensitivity analysis indicated the components that had the greatest impact on availability-for example, the failure time of the Standby Edge Server proved to be a very relevant component in the proposed architecture. The present work can help system architects develop distributed architectures considering points of failure and recovery measures.