Publikation: Artifical Intelligence Based Routing in...
Stammdaten
Titel: | Artifical Intelligence Based Routing in PLC Networks |
Untertitel: | |
Kurzfassung: | With innovation in network design, a strong rise in the specific performance for the end-to-end communication (capacity, latency, connectivity, etc) is expected. This paper tackles the possibility of using an artificial-intelligence-based algorithm to encompass smart routing in a network with a relatively low computation cost. The AI aspect of our method lies in the adaptability of the proposed algorithm: with the need of users and network characteristics changing in time and space, a smart, dynamic approach is required. The application of this AI is done in the specific framework of powerline communication (PLC) used as a front-hauling solution for different communication technologies. Training of the AI processor is done with synthetic data. A huge dataset is generated by using the transmission-line theory based approach to compute the capacity of a powerline link and its behavior with respect to topological information, such as disposition of nodes, their mutual distance and their overall density on the geographical territory. From this bottom-up-generated data, it is eventually possible to infer the capacity of each link in a network from its topological information, which is the only input the AI processor needs. |
Schlagworte: |
Publikationstyp: | Beitrag in Proceedings (Autorenschaft) |
Erscheinungsdatum: | 08.04.2018 (Online) |
Erschienen in: |
IEEE International Symposium on Power Line Communications - ISPLC 2018
IEEE International Symposium on Power Line Communications - ISPLC 2018
(
IEEE ComSoc;
)
zur Publikation |
Titel der Serie: | - |
Bandnummer: | - |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | S. 1 - 6 |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | 08.04.2018 |
ISBN (e-book): |
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eISSN: | - |
DOI: | http://dx.doi.org/10.1109/ISPLC.2018.8360241 |
Homepage: | https://ieeexplore.ieee.org/document/8360241/ |
Open Access |
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Zuordnung
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Fakultät für Technische Wissenschaften
Institut für Vernetzte und Eingebettete Systeme
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AT - 9020 Klagenfurt am Wörthersee |
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