Enabling and Leveraging AI in the Intelligent Edge: A Review of Current Trends and Future Directions
| Autor: | Filip De Turck, Tom Goethals, Bruno Volckaert |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
trends
Technology and Engineering Edge device Computer science POWER review TK5101-6720 Field (computer science) Software edge computing Taxonomy (general) fog networks BLOCKCHAIN Subdivision HE1-9990 ARCHITECTURE business.industry ARTIFICIAL-INTELLIGENCE ALGORITHMS PLATFORM General Medicine FRAMEWORK artificial intelligence Data science Variety (cybernetics) MODEL Market research edge networks Telecommunication Fog computing NEURAL-NETWORKS Enhanced Data Rates for GSM Evolution business Transportation and communications 5G |
| Zdroj: | IEEE Open Journal of the Communications Society, Vol 2, Pp 2311-2341 (2021) IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY |
| ISSN: | 2644-125X |
| Popis: | The use of AI on Smart applications and in the organization of the network edge presents a rapidly advancing research field, with a great variety of challenges and opportunities. This article aims to provide a holistic review of studies from 2019 to 2021 related to the Intelligent Edge, a concept comprising both the use of AI to organize edge networks (Edge Intelligence) and Smart applications in the edge. An introduction is given to the technologies required to understand the state of the art of AI in edge networks, and a taxonomy is provided with “Enabling Technology” for Edge Intelligence, “Organization” of the edge using AI, and AI “Applications” in the edge as its main topics. Research trend data from 2015 to 2020 is presented for various subdivisions of these topics, showing both absolute and relative research interest in each subtopic. The “Organization” aspect, being the main focus of this article, has a more fine-grained subdivision, explaining all contributing factors in detail. The trends indicate an exponential increase in research interest in nearly all subtopics, but significant differences between them. For each subdivision of the taxonomy a number of selected studies from 2019 to 2021 are gathered to form a high-level illustration of the state of the art of Edge Intelligence. From these selected studies and the trend data, a number of short-term challenges and high-level visions for Edge Intelligence are formulated, providing a basis for future work. |
| Databáze: | OpenAIRE |
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