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Adaptive and Fault-Tolerant Data Processing in Healthcare IoT Based on Fog Computing | IEEE Journals & Magazine | IEEE Xplore

Adaptive and Fault-Tolerant Data Processing in Healthcare IoT Based on Fog Computing


Abstract:

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-crit...Show More

Abstract:

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.
Published in: IEEE Transactions on Network Science and Engineering ( Volume: 7, Issue: 1, 01 Jan.-March 2020)
Page(s): 263 - 273
Date of Publication: 24 July 2018

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