Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen:
https://doi.org/10.21256/zhaw-26197
Publikationstyp: | Konferenz: Paper |
Art der Begutachtung: | Peer review (Publikation) |
Titel: | Priority-driven task processing in UAV-assisted software-defined edge networks |
Autor/-in: | Kalinagac, Onur Gür, Gürkan Alagöz, Fatih |
et. al: | No |
DOI: | 10.1109/GIIS56506.2022.9936953 10.21256/zhaw-26197 |
Tagungsband: | 2022 Global Information Infrastructure and Networking Symposium (GIIS) |
Seite(n): | 78 |
Seiten bis: | 84 |
Angaben zur Konferenz: | Global Information Infrastructure and Networking Symposium (GIIS), Argostoli, Greece, 26-28 September 2022 |
Erscheinungsdatum: | 2022 |
Verlag / Hrsg. Institution: | IEEE |
ISBN: | 978-1-6654-9095-5 |
Sprache: | Englisch |
Schlagwörter: | Aerial network; Edge computing; Task offloading; Unmanned Aerial Vehicle (UAV); Software-defined network; Vehicular network |
Fachgebiet (DDC): | 629: Luftfahrt- und Fahrzeugtechnik |
Zusammenfassung: | For providing wireless connectivity and facilitating a capacity boost under transient high service load situations, a substitute or auxiliary fast-deployable network is instrumental. Unmanned Aerial Vehicle (UAV) networks are well suited for such needs owing to their high mobility and agility. This paper considers a software-defined edge network consisting of UAVs equipped with wireless access points, which serve mobile users with latency-sensitive workload in an edge-to-cloud continuum setting. It investigates the task offloading paradigm to provide prioritized services via this on-demand aerial network. Accordingly, a task processing optimization model is defined to minimize the overall penalty calculated based on priority-weighted delay values against a priori defined task deadlines. Since the defined assignment problem is NP-hard, tailored heuristic models are proposed and evaluated to study how the system performs under different operating conditions. |
URI: | https://digitalcollection.zhaw.ch/handle/11475/26197 |
Volltext Version: | Akzeptierte Version |
Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
Departement: | School of Engineering |
Organisationseinheit: | Institut für Informatik (InIT) |
Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
---|---|---|---|---|
2022_Kalinagac-etal_Priority-driven-task-processing-edge-networks_GIIS2022.pdf | Accepted Version | 930.63 kB | Adobe PDF | Öffnen/Anzeigen |
Zur Langanzeige
Kalinagac, O., Gür, G., & Alagöz, F. (2022). Priority-driven task processing in UAV-assisted software-defined edge networks [Conference paper]. 2022 Global Information Infrastructure and Networking Symposium (GIIS), 78–84. https://doi.org/10.1109/GIIS56506.2022.9936953
Kalinagac, O., Gür, G. and Alagöz, F. (2022) ‘Priority-driven task processing in UAV-assisted software-defined edge networks’, in 2022 Global Information Infrastructure and Networking Symposium (GIIS). IEEE, pp. 78–84. Available at: https://doi.org/10.1109/GIIS56506.2022.9936953.
O. Kalinagac, G. Gür, and F. Alagöz, “Priority-driven task processing in UAV-assisted software-defined edge networks,” in 2022 Global Information Infrastructure and Networking Symposium (GIIS), 2022, pp. 78–84. doi: 10.1109/GIIS56506.2022.9936953.
KALINAGAC, Onur, Gürkan GÜR und Fatih ALAGÖZ, 2022. Priority-driven task processing in UAV-assisted software-defined edge networks. In: 2022 Global Information Infrastructure and Networking Symposium (GIIS). Conference paper. IEEE. 2022. S. 78–84. ISBN 978-1-6654-9095-5
Kalinagac, Onur, Gürkan Gür, and Fatih Alagöz. 2022. “Priority-Driven Task Processing in UAV-Assisted Software-Defined Edge Networks.” Conference paper. In 2022 Global Information Infrastructure and Networking Symposium (GIIS), 78–84. IEEE. https://doi.org/10.1109/GIIS56506.2022.9936953.
Kalinagac, Onur, et al. “Priority-Driven Task Processing in UAV-Assisted Software-Defined Edge Networks.” 2022 Global Information Infrastructure and Networking Symposium (GIIS), IEEE, 2022, pp. 78–84, https://doi.org/10.1109/GIIS56506.2022.9936953.
Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt, soweit nicht anderweitig angezeigt.