Adaptive and Fault-tolerant Data Processing in Healthcare IoT Based on Fog Computing
Adaptive and Fault-tolerant Data Processing in Healthcare IoT Based on Fog Computing
复制标题
基于雾计算的医疗物联网自适应容错数据处理
DOI：
10.1109/tnse.2018.2859307
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发表时间：
--
影响因子：
6.6
通讯作者：
Song Guo
中科院分区：
文献类型：
--
作者：
Kun Wang;Yun Shao;Lei Xie;Jie Wu;Song Guo
近年来，医疗物联网在很大程度上有助于缓解人口老龄化造成的医院和医疗资源压力。作为一个安全关键系统，医疗系统的快速反应是极其重要的。为了满足低延迟要求，雾计算是一种具有竞争力的解决方案，它将医疗物联网设备部署在云的边缘。然而，这些雾设备产生大量的传感器数据。设计一个特定的光纤陀螺设备框架，以确保可靠的数据传输和快速的数据处理成为一个至关重要的课题。为了提高数据传输的可靠性和处理速度，提出了一种基于简化可变邻域搜索（RVNS）的sEnsor数据处理框架（REDPF）。REDPF的功能包括容错数据传输，自适应滤波和数据负载减少处理。具体地说，一个可靠的传输机制，由自适应滤波器管理，将自动选择丢失或不准确的数据。在此基础上，设计了一种新的老年人健康状况评价方案。通过大量的模拟，我们表明，我们提出的方案提高了网络的可靠性，并提供了更快的处理速度。
In recent years, healthcare IoT have been helpful in mitigating pressures of hospital and medical resources caused by aging population to a large extent. As a safety-critical system, the rapid response from the health care system is extremely important. To fulfill the low latency requirement, fog computing is a competitive solution by deploying healthcare IoT devices on the edge of clouds. However, these fog devices generate huge amount of sensor data. Designing a specific framework for fog devices to ensure reliable data transmission and rapid data processing becomes a topic of utmost significance. In this paper, a Reduced Variable Neighborhood Search (RVNS)-based sEnsor Data Processing Framework (REDPF) is proposed to enhance reliability of data transmission and processing speed. Functionalities of REDPF include fault-tolerant data transmission, self-adaptive filtering and data-load-reduction processing. Specifically, a reliable transmission mechanism, managed by a self-adaptive filter, will recollect lost or inaccurate data automatically. Then, a new scheme is designed to evaluate the health status of the elderly people. Through extensive simulations, we show that our proposed scheme improves network reliability, and provides a faster processing speed.