Abstract

Abstract Telemedicine is one of the most rapidly developing areas of healthcare and it plays an increasing role in modern medicine. As the amount of data and demand for features increase, the data paths are becoming ever-more complex. Owing to this, it is vital in telemedicine to find a proper balance between consistency and availability under any given circumstances. However, making a trade-off can significantly influence the quality of the data. This study seeks to get an in-depth view of the problem by considering a real-world telemedicine use-case and elaborating the formal system specification of the scenario. After evaluating the specification, the constructed state graph is examined using graph coloring and other graph algorithms.

Highlights

  • Telemedicine is one of the most rapidly developing areas of healthcare and it plays an increasing role in modern medicine

  • Telemedicine systems are usually viewed as simple client-server architecture-based systems, the reasons and solutions mentioned above can lead to very complex data paths

  • This paper presents a concrete, active telemedicine use-case maintained by Inclouded [12], through which the formal system modeling and a new graph-based evaluation technique are performed

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Summary

Introduction

Telemedicine is one of the most rapidly developing areas of healthcare and it plays an increasing role in modern medicine. The extension of the CAP Theorem states that in the case of network Partitioning (P) a trade-off has to be made between Availability (A) and Consistency (C), but Else (E), when the system is running normally in the absence of partitions, another trade-off has to be made between Latency (L) and Consistency (C) The data goes through many stages, so the round-trip and the production of the visible data takes some time These latencies are external factors that are always present in these systems and play important roles. The formal modeling of a concrete telemedicine system that operates today and the evaluation of the system specification via model checking: the system specification consists of a client, a distributed database system, computational units and a cache. The nodes of the components contain information concerning the Quality of Data (QoD) limited by caching strategies and latency values; Analyzing the state graph of the system model with graph theoretical algorithms: the structure of the state graph components contains graph theoretically relevant information, and they can be applied for clustering

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