Pervasive healthcare is a promising assisted-living solution for chronic patients. However, current cutting-edge communication technologies are not able to strictly meet the requirements of these applications, especially in the case of life-threatening events. To bridge this gap, this article proposes a new architecture to support indoor healthcare monitoring, with a focus on epileptic patients. Several novel elements are introduced. The first element is the cascading of a WLAN and a cellular network, where IEEE 802.11ax is used for the wireless local area network to collect physiological and environmental data in-home and 5G-enabled Fixed Wireless Access links transfer them to a remote hospital. The second element is the extension of the network slicing concept to the WLAN, and the introduction of two new slice types to support both regular monitoring and emergency handling. Moreover, the inclusion of local computing capabilities at the WLAN router, together with a mobile edge computing resource, represents a further architectural enhancement. Local computation is required to trigger not only health-related alarms but also the network slicing change in case of emergency; in fact, proper radio resource scheduling is necessary for the cascaded networks to handle healthcare traffic together with other promiscuous everyday communication services. Numerical results demonstrate the effectiveness of the proposed approach while highlighting the performance gain achieved with respect to baseline solutions.

Martiradonna, S., Cisotto, G., Boggia, G., Piro, G., Vangelista, L., Tomasin, S. (2021). Cascaded WLAN-FWA Networking and Computing Architecture for Pervasive In-Home Healthcare. IEEE WIRELESS COMMUNICATIONS, 28(3), 92-99 [10.1109/MWC.001.2000330].

Cascaded WLAN-FWA Networking and Computing Architecture for Pervasive In-Home Healthcare

Giulia Cisotto
Secondo
;
2021

Abstract

Pervasive healthcare is a promising assisted-living solution for chronic patients. However, current cutting-edge communication technologies are not able to strictly meet the requirements of these applications, especially in the case of life-threatening events. To bridge this gap, this article proposes a new architecture to support indoor healthcare monitoring, with a focus on epileptic patients. Several novel elements are introduced. The first element is the cascading of a WLAN and a cellular network, where IEEE 802.11ax is used for the wireless local area network to collect physiological and environmental data in-home and 5G-enabled Fixed Wireless Access links transfer them to a remote hospital. The second element is the extension of the network slicing concept to the WLAN, and the introduction of two new slice types to support both regular monitoring and emergency handling. Moreover, the inclusion of local computing capabilities at the WLAN router, together with a mobile edge computing resource, represents a further architectural enhancement. Local computation is required to trigger not only health-related alarms but also the network slicing change in case of emergency; in fact, proper radio resource scheduling is necessary for the cascaded networks to handle healthcare traffic together with other promiscuous everyday communication services. Numerical results demonstrate the effectiveness of the proposed approach while highlighting the performance gain achieved with respect to baseline solutions.
Articolo in rivista - Articolo scientifico
Computer architecture; Medical services; 5G mobile communication; Wireless LAN; Biomedical monitoring; Wireless communication; Assisted living;
English
2021
28
3
92
99
9373012
none
Martiradonna, S., Cisotto, G., Boggia, G., Piro, G., Vangelista, L., Tomasin, S. (2021). Cascaded WLAN-FWA Networking and Computing Architecture for Pervasive In-Home Healthcare. IEEE WIRELESS COMMUNICATIONS, 28(3), 92-99 [10.1109/MWC.001.2000330].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/366702
Citazioni
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 5
Social impact