Microservices enabled bidirectional fault-tolerance scheme for healthcare internet of things
An immense volume of data is generated in smart health environments which can be managed through fog computing. Fog computing provides computing and storage services closer to the end user, making it an essential application for Healthcare Internet of Things (HIoT) devices. In HIoT, tasks such as Ca...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Published: |
2023
|
| Online Access: | http://scholars.utp.edu.my/id/eprint/37982/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178239465&doi=10.1007%2fs10586-023-04192-7&partnerID=40&md5=d906a41639cbceeaad5e7a997732bf2a |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Petronas |
| Summary: | An immense volume of data is generated in smart health environments which can be managed through fog computing. Fog computing provides computing and storage services closer to the end user, making it an essential application for Healthcare Internet of Things (HIoT) devices. In HIoT, tasks such as Cardiovascular Health Monitoring (CHM) which are highly sensitive to delays and failures and data are scheduled and managed by fog nodes. Timely detection and intervention in CHM are crucial during emergencies, such as suspected heart attacks, where rapid processing of physiological data and prompt triggering of alarms or notifications can save lives. A microservices-based approach is proposed in this study combining fog and cloud services. The proposed Two-Phase Fault Tolerant (TPFT) strategy for HIoT data management schedules and manages HIoT tasks on fog nodes in the first phase, while in the second phase, it implements a bidirectional fault-tolerant mechanism, covering task-aware fault tolerance and node-aware fault tolerance. Comparing the performance of TPFT with recent benchmarks, simulation results demonstrate that the proposed approach outperforms in terms latency, probability of failure rate, recovery time after failure, and extra resource utilization. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. |
|---|