Cargando…
An Architecture for the Performance Management of Smart Healthcare Applications
The sixth-generation (6G) network intends to revolutionize the healthcare sector. It will offer smart healthcare (s-health) treatments and allow efficient patient remote monitoring, exposing the high potential of 6G communication technology in telesurgery, epidemic, and pandemic. Healthcare relies o...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582713/ https://www.ncbi.nlm.nih.gov/pubmed/32998439 http://dx.doi.org/10.3390/s20195566 |
_version_ | 1783599255012769792 |
---|---|
author | Vergütz, Andressa G. Prates, Nelson Henrique Schwengber, Bruno Santos, Aldri Nogueira, Michele |
author_facet | Vergütz, Andressa G. Prates, Nelson Henrique Schwengber, Bruno Santos, Aldri Nogueira, Michele |
author_sort | Vergütz, Andressa |
collection | PubMed |
description | The sixth-generation (6G) network intends to revolutionize the healthcare sector. It will offer smart healthcare (s-health) treatments and allow efficient patient remote monitoring, exposing the high potential of 6G communication technology in telesurgery, epidemic, and pandemic. Healthcare relies on 6G communication technology, diminishing barriers as time and space. S-health applications require strict network requirements, for instance, 99.999% of service reliability and 1 ms of end-to-end latency. However, it is a challenging task to manage network resources and applications towards such performance requirements. Hence, significant attention focuses on performance management as a way of searching for efficient approaches to adjust and tune network resources to application needs, assisting in achieving the required performance levels. In the literature, performance management employs techniques such as resource allocation, resource reservation, traffic shaping, and traffic scheduling. However, they are dedicated to specific problems such as resource allocation for a particular device, ignoring the heterogeneity of network devices, and communication technology. Thus, this article presents PRIMUS, a performance management architecture that aims to meet the requirements of low-latency and high-reliability in an adaptive way for s-health applications. As network slicing is central to realizing the potential of 5G–6G networks, PRIMUS manages traffic through network slicing technologies. Unlike existing proposals, it supports device and service heterogeneity based on the autonomous knowledge of s-health applications. Emulation results in Mininet-WiFi show the feasibility of meeting the s-health application requirements in virtualized environments. |
format | Online Article Text |
id | pubmed-7582713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75827132020-10-28 An Architecture for the Performance Management of Smart Healthcare Applications Vergütz, Andressa G. Prates, Nelson Henrique Schwengber, Bruno Santos, Aldri Nogueira, Michele Sensors (Basel) Article The sixth-generation (6G) network intends to revolutionize the healthcare sector. It will offer smart healthcare (s-health) treatments and allow efficient patient remote monitoring, exposing the high potential of 6G communication technology in telesurgery, epidemic, and pandemic. Healthcare relies on 6G communication technology, diminishing barriers as time and space. S-health applications require strict network requirements, for instance, 99.999% of service reliability and 1 ms of end-to-end latency. However, it is a challenging task to manage network resources and applications towards such performance requirements. Hence, significant attention focuses on performance management as a way of searching for efficient approaches to adjust and tune network resources to application needs, assisting in achieving the required performance levels. In the literature, performance management employs techniques such as resource allocation, resource reservation, traffic shaping, and traffic scheduling. However, they are dedicated to specific problems such as resource allocation for a particular device, ignoring the heterogeneity of network devices, and communication technology. Thus, this article presents PRIMUS, a performance management architecture that aims to meet the requirements of low-latency and high-reliability in an adaptive way for s-health applications. As network slicing is central to realizing the potential of 5G–6G networks, PRIMUS manages traffic through network slicing technologies. Unlike existing proposals, it supports device and service heterogeneity based on the autonomous knowledge of s-health applications. Emulation results in Mininet-WiFi show the feasibility of meeting the s-health application requirements in virtualized environments. MDPI 2020-09-28 /pmc/articles/PMC7582713/ /pubmed/32998439 http://dx.doi.org/10.3390/s20195566 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vergütz, Andressa G. Prates, Nelson Henrique Schwengber, Bruno Santos, Aldri Nogueira, Michele An Architecture for the Performance Management of Smart Healthcare Applications |
title | An Architecture for the Performance Management of Smart Healthcare Applications |
title_full | An Architecture for the Performance Management of Smart Healthcare Applications |
title_fullStr | An Architecture for the Performance Management of Smart Healthcare Applications |
title_full_unstemmed | An Architecture for the Performance Management of Smart Healthcare Applications |
title_short | An Architecture for the Performance Management of Smart Healthcare Applications |
title_sort | architecture for the performance management of smart healthcare applications |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582713/ https://www.ncbi.nlm.nih.gov/pubmed/32998439 http://dx.doi.org/10.3390/s20195566 |
work_keys_str_mv | AT vergutzandressa anarchitecturefortheperformancemanagementofsmarthealthcareapplications AT gpratesnelson anarchitecturefortheperformancemanagementofsmarthealthcareapplications AT henriqueschwengberbruno anarchitecturefortheperformancemanagementofsmarthealthcareapplications AT santosaldri anarchitecturefortheperformancemanagementofsmarthealthcareapplications AT nogueiramichele anarchitecturefortheperformancemanagementofsmarthealthcareapplications AT vergutzandressa architecturefortheperformancemanagementofsmarthealthcareapplications AT gpratesnelson architecturefortheperformancemanagementofsmarthealthcareapplications AT henriqueschwengberbruno architecturefortheperformancemanagementofsmarthealthcareapplications AT santosaldri architecturefortheperformancemanagementofsmarthealthcareapplications AT nogueiramichele architecturefortheperformancemanagementofsmarthealthcareapplications |