This review analyzes latency optimization in healthcare IoT, highlighting fog computing's role in enhancing performance and addressing key challenges.
The Healthcare Internet of Things (H-IoT) has made significant strides in transforming remote diagnostics, real-time monitoring, and data collection. However, achieving low latency remains a challenge, even for systems that critically depend on it, such as emergency response systems and remote surgeries. Fog computing (FC) emerges as a promising solution to mitigate latency issues by bringing computational resources closer to edge devices. This review provides a comprehensive analysis of latency optimization approaches within the H-IoT, framed within the context of FC. The study focuses on architectural enhancements, data communication methods, resource management strategies, and load distribution techniques aimed at reducing latency. Additionally, it evaluates existing challenges related to energy efficiency and trade-offs, security considerations, and scalability potential. Based on an analysis of recent advancements in the field, this study outlines potential development trends and future research directions for building adaptive, fast, and secure H-IoT systems. The study reaffirms the pivotal role of FC in shaping the future of healthcare services, particularly those with stringent low-latency requirements.
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Jaaz et al. (2025) studied this question.
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