Fog-Enabled Smart Health: Toward Cooperative and Secure Healthcare Service Provision

Tang, Wenjuan; Zhang, Kuan; Zhang, Deyu; Ren, Ju; Zhang, Yaoxue; Shen, Xuemin

doi:10.1109/mcom.2019.1800234

Cited by 51 publications

(30 citation statements)

References 13 publications

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“…Current studies employ concepts of fog computing for e-Health applications with different goals. Table 3 summarizes and classifies these research initiatives according to their main tasks, which are: (i) data collection [74][75][76][77][78]; (ii) data processing [71,[79][80][81][82][83][84]; (iii) critical data analysis [31,42,44,[85][86][87]; and (iv) real-time feedback [49,61,[88][89][90][91]. Such functionalities in medical services focus on the enhancements of the security and privacy of sensitive information.…”

Section: Discussionmentioning

confidence: 99%

“…A group of articles focuses on the critical data analysis class, which considers strategies in which the main focus is to analyze data from critical conditions. In this scope, the authors in [85] demonstrated concerns regarding the security of patients data. They designed a fog-enabled architecture for healthcare services with a focus on risk assessment and information sharing.…”

Section: Critical Data Analysismentioning

confidence: 99%

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Looking at Fog Computing for E-Health through the Lens of Deployment Challenges and Applications

Vilela

Rodrigues

Righi

et al. 2020

Sensors

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Fog computing is a distributed infrastructure where specific resources are managed at the network border using cloud computing principles and technologies. In contrast to traditional cloud computing, fog computing supports latency-sensitive applications with less energy consumption and a reduced amount of data traffic. A fog device is placed at the network border, allowing data collection and processing to be physically close to their end-users. This characteristic is essential for applications that can benefit from improved latency and response time. In particular, in the e-Health field, many solutions rely on real-time data to monitor environments, patients, and/or medical staff, aiming at improving processes and safety. Therefore, fog computing can play an important role in such environments, providing a low latency infrastructure. The main goal of the current research is to present fog computing strategies focused on electronic-Health (e-Health) applications. To the best of our knowledge, this article is the first to propose a review in the scope of applications and challenges of e-Health fog computing. We introduce some of the available e-Health solutions in the literature that focus on latency, security, privacy, energy efficiency, and resource management techniques. Additionally, we discuss communication protocols and technologies, detailing both in an architectural overview from the edge devices up to the cloud. Differently from traditional cloud computing, the fog concept demonstrates better performance in terms of time-sensitive requirements and network data traffic. Finally, based on the evaluation of the current technologies for e-Health, open research issues and challenges are identified, and further research directions are proposed.

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Section: Discussionmentioning

confidence: 99%

Section: Critical Data Analysismentioning

confidence: 99%

Looking at Fog Computing for E-Health through the Lens of Deployment Challenges and Applications

Vilela

Rodrigues

Righi

et al. 2020

Sensors

View full text Add to dashboard Cite

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“…Edge-based IoT healthcare frameworks generally involve remote monitoring systems that exploit different types of smart sensors for the implementation of healthcare systems that are diagnostic, sensitive, and preventive [1], [38][39][40]. In most recent studies, fog computing nodes work as local servers: they gather, analyze, and process health IoT sensor data and give rapid-response services [41]. For many years, healthcare researchers have been exploring solutions for the remote monitoring of patients and for the transmission of health reports to provide clinicians with patient data in real time.…”

Section: Edge Iot Smart Healthcare Architecturementioning

confidence: 99%

Edge Intelligence and Internet of Things in Healthcare: A Survey

2021

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“…The use of Fog/Edge computing architectures in the health care domain typically deals with the design of remote monitoring solutions that leverage wearable and field sensor networks for implementing protective, preventive and responsive systems [3] . In this context, most contributions involve fog nodes acting as local servers that collect and process health data to quickly respond to the service requirements [49] . The scientific community has been investigating for more than ten years solutions for monitoring patients' health status with the aim of remotely providing reports to clinicians.…”

Section: A General Architecture For Iomt Systemsmentioning

confidence: 99%

Trends in IoT based solutions for health care: Moving AI to the edge

Greco

Percannella

Ritrovato

et al. 2020

Pattern Recognition Letters

246

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In recent times, we assist to an ever growing diffusion of smart medical sensors and Internet of things devices that are heavily changing the way healthcare is approached worldwide. In this context, a combination of Cloud and IoT architectures is often exploited to make smart healthcare systems capable of supporting near realtime applications when processing and performing Artificial Intelligence on the huge amount of data produced by wearable sensor networks. Anyway, the response time and the availability of cloud based systems, together with security and privacy, still represent critical issues that prevents Internet of Medical Things (IoMT) devices and architectures from being a reliable and effective solution to the aim. Lately, there is a growing interest towards architectures and approaches that exploit Edge and Fog computing as an answer to compensate the weaknesses of the cloud. In this paper, we propose a short review about the general use of IoT solutions in health care, starting from early health monitoring solutions from wearable sensors up to a discussion about the latest trends in fog/edge computing for smart health.

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Fog-Enabled Smart Health: Toward Cooperative and Secure Healthcare Service Provision

Cited by 51 publications

References 13 publications

Looking at Fog Computing for E-Health through the Lens of Deployment Challenges and Applications

Looking at Fog Computing for E-Health through the Lens of Deployment Challenges and Applications

Edge Intelligence and Internet of Things in Healthcare: A Survey

Trends in IoT based solutions for health care: Moving AI to the edge

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