Virtualizing AI at the Distributed Edge towards Intelligent IoT Applications
Several Internet of Things (IoT) applications are booming which rely on advanced artificial intelligence (AI) and, in particular, machine learning (ML) algorithms to assist the users and make decisions on their behalf in a large variety of contexts, such as smart homes, smart cities, smart factories...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Journal of Sensor and Actuator Networks |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2224-2708/10/1/13 |
| _version_ | 1827601865405104128 |
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| author | Claudia Campolo Giacomo Genovese Antonio Iera Antonella Molinaro |
| author_facet | Claudia Campolo Giacomo Genovese Antonio Iera Antonella Molinaro |
| author_sort | Claudia Campolo |
| collection | DOAJ |
| description | Several Internet of Things (IoT) applications are booming which rely on advanced artificial intelligence (AI) and, in particular, machine learning (ML) algorithms to assist the users and make decisions on their behalf in a large variety of contexts, such as smart homes, smart cities, smart factories. Although the traditional approach is to deploy such compute-intensive algorithms into the centralized cloud, the recent proliferation of low-cost, AI-powered microcontrollers and consumer devices paves the way for having the intelligence pervasively spread along the cloud-to-things continuum. The take off of such a promising vision may be hurdled by the resource constraints of IoT devices and by the heterogeneity of (mostly proprietary) AI-embedded software and hardware platforms. In this paper, we propose a solution for the AI distributed deployment at the deep edge, which lays its foundation in the IoT virtualization concept. We design a <i>virtualization layer</i> hosted at the network edge that is in charge of the semantic description of AI-embedded IoT devices, and, hence, it can expose as well as augment their cognitive capabilities in order to feed intelligent IoT applications. The proposal has been mainly devised with the twofold aim of (i) relieving the pressure on constrained devices that are solicited by multiple parties interested in accessing their generated data and inference, and (ii) and targeting interoperability among AI-powered platforms. A Proof-of-Concept (PoC) is provided to showcase the viability and advantages of the proposed solution. |
| first_indexed | 2024-03-09T05:05:30Z |
| format | Article |
| id | doaj.art-e222f9784f0441e08c995b6a02767202 |
| institution | Directory Open Access Journal |
| issn | 2224-2708 |
| language | English |
| last_indexed | 2024-03-09T05:05:30Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Sensor and Actuator Networks |
| spelling | doaj.art-e222f9784f0441e08c995b6a027672022023-12-03T12:55:58ZengMDPI AGJournal of Sensor and Actuator Networks2224-27082021-02-011011310.3390/jsan10010013Virtualizing AI at the Distributed Edge towards Intelligent IoT ApplicationsClaudia Campolo0Giacomo Genovese1Antonio Iera2Antonella Molinaro3The Department of Information, Infrastructures and Sustainable Energy (DIIES) Department, University Mediterranea of Reggio Calabria, 89100 Reggio Calabria, ItalyThe Department of Information, Infrastructures and Sustainable Energy (DIIES) Department, University Mediterranea of Reggio Calabria, 89100 Reggio Calabria, ItalyThe Department of Information, Infrastructures and Sustainable Energy (DIIES) Department, University of Calabria, 87036 Rende, ItalyThe Department of Information, Infrastructures and Sustainable Energy (DIIES) Department, University Mediterranea of Reggio Calabria, 89100 Reggio Calabria, ItalySeveral Internet of Things (IoT) applications are booming which rely on advanced artificial intelligence (AI) and, in particular, machine learning (ML) algorithms to assist the users and make decisions on their behalf in a large variety of contexts, such as smart homes, smart cities, smart factories. Although the traditional approach is to deploy such compute-intensive algorithms into the centralized cloud, the recent proliferation of low-cost, AI-powered microcontrollers and consumer devices paves the way for having the intelligence pervasively spread along the cloud-to-things continuum. The take off of such a promising vision may be hurdled by the resource constraints of IoT devices and by the heterogeneity of (mostly proprietary) AI-embedded software and hardware platforms. In this paper, we propose a solution for the AI distributed deployment at the deep edge, which lays its foundation in the IoT virtualization concept. We design a <i>virtualization layer</i> hosted at the network edge that is in charge of the semantic description of AI-embedded IoT devices, and, hence, it can expose as well as augment their cognitive capabilities in order to feed intelligent IoT applications. The proposal has been mainly devised with the twofold aim of (i) relieving the pressure on constrained devices that are solicited by multiple parties interested in accessing their generated data and inference, and (ii) and targeting interoperability among AI-powered platforms. A Proof-of-Concept (PoC) is provided to showcase the viability and advantages of the proposed solution.https://www.mdpi.com/2224-2708/10/1/13Internet of Thingsedge computingvirtualizationedge AIartificial intelligenceTinyML |
| spellingShingle | Claudia Campolo Giacomo Genovese Antonio Iera Antonella Molinaro Virtualizing AI at the Distributed Edge towards Intelligent IoT Applications Journal of Sensor and Actuator Networks Internet of Things edge computing virtualization edge AI artificial intelligence TinyML |
| title | Virtualizing AI at the Distributed Edge towards Intelligent IoT Applications |
| title_full | Virtualizing AI at the Distributed Edge towards Intelligent IoT Applications |
| title_fullStr | Virtualizing AI at the Distributed Edge towards Intelligent IoT Applications |
| title_full_unstemmed | Virtualizing AI at the Distributed Edge towards Intelligent IoT Applications |
| title_short | Virtualizing AI at the Distributed Edge towards Intelligent IoT Applications |
| title_sort | virtualizing ai at the distributed edge towards intelligent iot applications |
| topic | Internet of Things edge computing virtualization edge AI artificial intelligence TinyML |
| url | https://www.mdpi.com/2224-2708/10/1/13 |
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