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<p>The current healthcare system struggles to respond quickly enough to provide emergency medical care, particularly in remote or densely populated areas, or cannot scale to adequate levels of response in real-time. This paper presents an elaborate adaptive edge-fog healthcare network framework that supports Electronic Medical Records (EMR) through a multi-layer optimised solution. It also includes a real-time, decentralised processing model based on edge and fog computing architectures, which avoids the high latency typically required by most cloud-based systems when processing important data closer to its origin. To achieve this end, several novel features have been proposed within this framework, including a dynamic resource allocation algorithm that balances the computational load on the target edge and/or fog nodes as necessary to achieve optimal performance and prevent system failure. Furthermore, the operational environment of the framework incorporates robust and reliable methods for fault tolerance and data protection against leakage, even in low-connectivity networks or with node loss. Large-scale experiments demonstrate that the framework achieves a latency reduction rate of 66.67%, an energy consumption improvement of 92%, and a reliability of 96% in failure cases, thereby outcompeting cloud-only architectures in disaster recovery scenarios. Interestingly, the findings presented can demonstrate how the framework’s utilization may revolutionise healthcare emergency management by offering fast, safe, and efficient data-supported assistance in various care contexts.</p>

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Adaptive edge-fog healthcare networks: a novel framework for emergency response management

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月30日

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  • Ahmed M. Alwakeel

摘要

The current healthcare system struggles to respond quickly enough to provide emergency medical care, particularly in remote or densely populated areas, or cannot scale to adequate levels of response in real-time. This paper presents an elaborate adaptive edge-fog healthcare network framework that supports Electronic Medical Records (EMR) through a multi-layer optimised solution. It also includes a real-time, decentralised processing model based on edge and fog computing architectures, which avoids the high latency typically required by most cloud-based systems when processing important data closer to its origin. To achieve this end, several novel features have been proposed within this framework, including a dynamic resource allocation algorithm that balances the computational load on the target edge and/or fog nodes as necessary to achieve optimal performance and prevent system failure. Furthermore, the operational environment of the framework incorporates robust and reliable methods for fault tolerance and data protection against leakage, even in low-connectivity networks or with node loss. Large-scale experiments demonstrate that the framework achieves a latency reduction rate of 66.67%, an energy consumption improvement of 92%, and a reliability of 96% in failure cases, thereby outcompeting cloud-only architectures in disaster recovery scenarios. Interestingly, the findings presented can demonstrate how the framework’s utilization may revolutionise healthcare emergency management by offering fast, safe, and efficient data-supported assistance in various care contexts.