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Joint Communication and Computing Optimization for Digital Twin Synchronization with Aerial Relay

Wang, Yi ; Krantzik, Markus ; Xiang, Lin ; Klein, Anja (2024)
Joint Communication and Computing Optimization for Digital Twin Synchronization with Aerial Relay.
59th IEEE Internartional Conference on Communications (ICC'24). Denver, USA (09.06.2024 - 13.06.2024)
doi: 10.1109/ICC51166.2024.10622630
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Digital twin (DT) applications usually need to be synchronized in real time with the state of the physical system (PS). This process includes both synchronizing the data collected by sensors in the PS to a server and updating the DT at the server in adaptation to the dynamics of the PS. However, communicating with power- and rate-limited sensors and processing high-volume sensed data with limited computing resources present significant challenges for DT synchronization. In this paper, we tackle both bottlenecks by proposing a joint communication and computing design for DT synchronization. In particular, we exploit buffering at an aerial cluster head of the sensors and enable buffer-aided (BA) relaying to increase the communication throughput of the sensors during data synchronization. Moreover, we adopt a novel stream computing scheme, which allows for DT updating in parallel with data synchronization, to accelerate DT synchronization. To maximize the performance of the proposed approach, we jointly optimize the trajectory of the aerial relay and the communication and computing resource allocation for minimizing the DT synchronization time. The formulated problem is a mixed-integer nonconvex problem, which is generally intractable. To tackle this challenge, we propose a low-complexity two-layer iterative suboptimal algorithm. Our simulation results show that the DT synchronization time can be significantly reduced by up to 43.8%, through stream computing and the joint optimization of the relay's trajectory and the communication/computing resource allocation.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2024
Autor(en): Wang, Yi ; Krantzik, Markus ; Xiang, Lin ; Klein, Anja
Art des Eintrags: Bibliographie
Titel: Joint Communication and Computing Optimization for Digital Twin Synchronization with Aerial Relay
Sprache: Englisch
Publikationsjahr: 20 August 2024
Verlag: IEEE
Buchtitel: ICC 2024 - IEEE International Conference on Communications
Veranstaltungstitel: 59th IEEE Internartional Conference on Communications (ICC'24)
Veranstaltungsort: Denver, USA
Veranstaltungsdatum: 09.06.2024 - 13.06.2024
DOI: 10.1109/ICC51166.2024.10622630
Kurzbeschreibung (Abstract):

Digital twin (DT) applications usually need to be synchronized in real time with the state of the physical system (PS). This process includes both synchronizing the data collected by sensors in the PS to a server and updating the DT at the server in adaptation to the dynamics of the PS. However, communicating with power- and rate-limited sensors and processing high-volume sensed data with limited computing resources present significant challenges for DT synchronization. In this paper, we tackle both bottlenecks by proposing a joint communication and computing design for DT synchronization. In particular, we exploit buffering at an aerial cluster head of the sensors and enable buffer-aided (BA) relaying to increase the communication throughput of the sensors during data synchronization. Moreover, we adopt a novel stream computing scheme, which allows for DT updating in parallel with data synchronization, to accelerate DT synchronization. To maximize the performance of the proposed approach, we jointly optimize the trajectory of the aerial relay and the communication and computing resource allocation for minimizing the DT synchronization time. The formulated problem is a mixed-integer nonconvex problem, which is generally intractable. To tackle this challenge, we propose a low-complexity two-layer iterative suboptimal algorithm. Our simulation results show that the DT synchronization time can be significantly reduced by up to 43.8%, through stream computing and the joint optimization of the relay's trajectory and the communication/computing resource allocation.

Freie Schlagworte: BMBF Open6GHub, DAAD, emergenCITY, emergenCITY_KOM
Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Kommunikationstechnik
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
Hinterlegungsdatum: 25 Okt 2024 12:46
Letzte Änderung: 25 Okt 2024 12:46
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