Performance Prediction of Store and Forward Telemedicine Using Graph Theoretic Approach of Symmetry Queueing Network
Subramani Palani Niranjan, K R N Aswini, Sorin Vlase, Maria Luminița Scutaru · Symmetry · 2025
In the evolving landscape of healthcare, telemedicine has emerged as a transformative solution, effectively bridging gaps in medical service delivery across diverse geographic regions. Particularly in rural areas, where access to immediate and specialized care remains limited, store-and-forward telemedicine provides a powerful and practical approach. In rural emergency healthcare settings, resource limitations, specialist shortages, and unreliable connectivity frequently delay critical medical interventions. To address these challenges, this study proposes a store-and-forward telemedicine framework optimized through the use of queueing networks, aiming to enhance emergency response efficiency. The proposed model is structured as a four-node system comprising initial registration, consultation, diagnosis, and treatment. Each node operates as a service queue where patient data are sequentially collected, prioritized, and forwarded. By employing an open queueing network structure, the model devises steady-state probabilities for the number of patients at each node, facilitating a detailed performance analysis of patient flows. Symmetry plays a critical role in maintaining patient flow balance and system stability within the store-and-forward telemedicine model. When the routing probabilities between nodes are balanced, the queueing network exhibits probabilistic symmetry, ensuring consistent transition behavior. Moreover, the directed graph representation of the system demonstrates structural symmetry, reflecting identical service times at all nodes and uniform transition probabilities between nodes. Incorporating the concept of symmetry enables a simplified analytical approach, reduces computational complexity, and provides a more accurate approximation model for evaluating system performance.