Reliability for Smart Healthcare: A Network Slicing Perspective
Autor: | Michele Nogueira, Guevara Noubir, Andressa Vergutz |
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Rok vydání: | 2020 |
Předmět: |
Telemedicine
Computer Networks and Communications Computer science business.industry Wearable computer 020206 networking & telecommunications 02 engineering and technology Slicing Personalization Cost reduction Risk analysis (engineering) Hardware and Architecture Health care 0202 electrical engineering electronic engineering information engineering Architecture business Software Reliability (statistics) Information Systems |
Zdroj: | IEEE Network. 34:91-97 |
ISSN: | 1558-156X 0890-8044 |
DOI: | 10.1109/mnet.011.1900458 |
Popis: | Pursuing improvements in the healthcare system is mandatory for its efficiency and cost reduction. The fast popularization of implantable and wearable sensors promotes the diversity of healthcare applications and services, ranging from real-time and critical care monitoring to telemedicine. For smart healthcare (s-health), reliability plays an essential role, given the sensitivity of its data and services. In this article, we envision an architecture based on network slicing that can provide reliability for s-health applications and services. The architecture relies on fingerprinting healthcare applications to quickly customize resources and meet the level of reliability required for each s-health application. A fingerprinting study case is presented for s-health, based on a dataset containing real traffic. Results show that application fingerprinting reaches 90 percent accuracy, assisting in network customization. Finally, we discuss the main open issues and opportunities that network slicing technology provides for s-health. |
Databáze: | OpenAIRE |
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