Pasquale Pace
An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0
Pace, Pasquale; Aloi, Gianluca; Gravina, Raffaele; Caliciuri, Giuseppe; Fortino, Giancarlo; Liotta, Antonio
Authors
Gianluca Aloi
Raffaele Gravina
Giuseppe Caliciuri
Giancarlo Fortino
Antonio Liotta
Abstract
Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard cloud-based approaches to reduce the interaction timing and the huge amount of data coming from Internet of Things (IoT) devices toward the Internet. In the next future, Edge-based approaches will be essential to support time-dependent applications in the Industry 4.0 context; thus, the paper proposes BodyEdge, a novel architecture well suited for human-centric applications, in the context of the emerging healthcare industry. It consists of a tiny mobile client module and a performing edge gateway supporting multiradio and multitechnology communication to collect and locally process data coming from different scenarios; moreover, it also exploits the facilities made available from both private and public cloud platforms to guarantee a high flexibility, robustness, and adaptive service level. The advantages of the designed software platform have been evaluated in terms of reduced transmitted data and processing time through a real implementation on different hardware platforms. The conducted study also highlighted the network conditions (data load and processing delay) in which BodyEdge is a valid and inexpensive solution for healthcare application scenarios.
Journal Article Type | Article |
---|---|
Acceptance Date | May 27, 2018 |
Online Publication Date | Jun 1, 2018 |
Publication Date | 2019-01 |
Deposit Date | Jul 29, 2019 |
Publicly Available Date | Aug 6, 2019 |
Journal | IEEE Transactions on Industrial Informatics |
Print ISSN | 1551-3203 |
Electronic ISSN | 1941-0050 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 15 |
Issue | 1 |
Pages | 481-489 |
DOI | https://doi.org/10.1109/tii.2018.2843169 |
Keywords | Body sensor networks, cloud computing, edge computing, heart rate variability, internet of things |
Public URL | http://researchrepository.napier.ac.uk/Output/1995589 |
Publisher URL | https://doi.org/10.1109%2Ftii.2018.2843169 |
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An Edge-Based Architecture To Support Efficient Applications For Healthcare Industry 4.0
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