An IPv6-based framework for fog-assisted healthcare monitoring

Jianqiang Hu,Wei Liang,Keshou Wu

doi:10.1177/1687814018819515

Jianqiang Hu, Wei Liang + Show 1 more

Open Access

https://doi.org/10.1177/1687814018819515

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Abstract

The new generation healthcare monitoring system combines technologies of wireless body sensor network, cloud computing, and Bigdata, and there are still limitations in protocol security, response delay, and prediction of potential severity disease. In response to the above situation, an Internet Protocol Version 6 (IPv6)-based framework for fog-assisted healthcare monitoring is proposed. This framework is composite of body-sensing layer, fog layer, and cloud layer. The body-sensing layer generates physiological data, and fog computing node in fog layer collects and analyses time-sensitive data. Fog layer sends physiological data to cloud computing node in cloud layer for further processing. Mobile intelligent device connects fog computing node and helps individuals to predict the potential disease with its level of severity. The proposed framework uses advanced techniques such as IPv6-based network architecture, cloud–fog resource scheduling algorithm based on time threshold, and classification model of chronic diseases based on cascaded deep learning and so on. In order to determine the validity of the framework, health data were systematically generated from 45 patients for 30 days. Results depict that the proposed classification model of chronic diseases has high accuracy in determining the level of severity of potential disease. Moreover, response delay is much lower than Internet Protocol Version 4 (IPv4)-based cloud-assisted environment.

Highlights

The increasing population and chronic diseases bring high pressure on quality and quantity of healthcare
The main contributions of this paper include: [1] proposing an enable framework for Internet Protocol Version 6 (IPv6)-based fog-assisted healthcare monitoring; [2] forming an IPv6-based network architecture; [3] scheduling cloud–fog resource based on time threshold to reduce response delay; [4] proposing classification model of chronic diseases based on cascaded deep learning; [5] developing prototype system to prevent cardiovascular disease (CVD) or quickly respond to the occurrence of disease and accidents
Fog computing node performs protocol conversion and provides other higher level services such as data aggregation and dimensionality reduction, and classification model of chronic diseases based on cascaded deep learning

Summary

Introduction

The increasing population and chronic diseases bring high pressure on quality and quantity of healthcare. In order to overcome protocol security, network latency, and prediction of potential severity disease of IPv4-based cloud-assisted healthcare monitoring, some nascent technologies are introduced as follows: 1. The main contributions of this paper include: [1] proposing an enable framework for IPv6-based fog-assisted healthcare monitoring; [2] forming an IPv6-based network architecture; [3] scheduling cloud–fog resource based on time threshold to reduce response delay; [4] proposing classification model of chronic diseases based on cascaded deep learning; [5] developing prototype system to prevent CVD or quickly respond to the occurrence of disease and accidents. Section ‘‘Conclusion’’ concludes the paper with some appropriate remarks

Related works

Consider the following classifier

Experimental setup and analysis

Findings

Conclusion