A local external coupling matrix solution and dynamic processing in medical cyber-physical cloud systems

Medical cyber-physical cloud systems (MCPCS) are new generation medical cyber-physical systems (MCPS), which introduce cloud computing to integrate multiple MCPS to improve quality of service (QoS) and expand service scope in hospitals. When used in large-scale distributed environment, MCPCS need to perform a stability analysis to guarantee collaboration among multiple MCPS. In this paper, we propose a local topology search algorithm (LTS) to obtain the local external coupling matrices, which are important input parameters for the local synchronization stability analysis of MCPCS. LTS generates an optimal multi-fork tree from the source end MCPS to multiple destination end MCPS. Based on the relationship between nodes in the optimal multi-fork tree, the local external coupling matrices applied to the local synchronization stability analysis of MCPCS are then solved. Considering the variability of network topology, we further propose a dynamic processing method called external coupling matrix change processing (ECMCP) to ensure the real-time update of the local external coupling matrices and dimensional consistency. Experimental results show that the proposed solution of LTS & ECMCP has lower costs of nodes and their communications than existing method.