Ejaz, M.; Kumar, T.; Kovacevic, I.; Ylianttila, M.; Harjula, E. Health-BlockEdge: Blockchain-Edge Framework for Reliable Low-Latency Digital Healthcare Applications. Sensors 2021, 21, 2502. https://doi.org/10.3390/s21072502
Health-BlockEdge : blockchain-edge framework for reliable low-latency digital healthcare applications
|Author:||Ejaz, Muneeb1; Kumar, Tanesh1; Kovacevic, Ivana1;|
1Erkki Koiso-Kanttilan Katu 3, University of Oulu, Linnanmaa, 90570 Oulu, Finland
|Online Access:||PDF Full Text (PDF, 3.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021042712889
Multidisciplinary Digital Publishing Institute,
|Publish Date:|| 2021-04-27
The rapid evolution of technology allows the healthcare sector to adopt intelligent, context-aware, secure, and ubiquitous healthcare services. Together with the global trend of an aging population, it has become highly important to propose value-creating, yet cost-efficient digital solutions for healthcare systems. These solutions should provide effective means of healthcare services in both the hospital and home care scenarios. In this paper, we focused on the latter case, where the goal was to provide easy-to-use, reliable, and secure remote monitoring and aid for elderly persons at their home. We proposed a framework to integrate the capabilities of edge computing and blockchain technology to address some of the key requirements of smart remote healthcare systems, such as long operating times, low cost, resilience to network problems, security, and trust in highly dynamic network conditions. In order to assess the feasibility of our approach, we evaluated the performance of our framework in terms of latency, power consumption, network utilization, and computational load, compared to a scenario where no blockchain was used.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research was conducted within DigiHealth, 5Gear and 6G Flagship projects, funded by the Academy of Finland.
© The Authors 2021. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.