A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC

Sabarish Krishna Moorthy; Ankush Harindranath; Maxwell McManus; Zhangyu Guan; Nicholas Mastronarde; Elizabeth Serena Bentley; Michael Medley

doi:10.1109/DCOSS54816.2022.00059

A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC

Sabarish Krishna Moorthy, Ankush Harindranath, Maxwell McManus, Zhangyu Guan, Nicholas Mastronarde, Elizabeth Serena Bentley, Michael Medley

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

Data-driven control based on AI/ML techniques has a great potential to enable zero-touch automated modeling, optimization and control of complex wireless systems. However, it is challenging to collect network traces in the real world because of high time and labor cost, weather limitations as well as safety concerns. In this work we attempt to tackle this challenge by designing a multi-fidelity simulator taking wireless Unmanned Aerial Vehicle (UAV) networks into consideration. We design the simulator by interfacing two Unmanned Aerial System (UAS) simulators we have developed in prior years: UBSim and UB-ANC. The former focuses on UAV network optimization and policy training by considering explicitly the network environments such as blockage dynamics, while the latter focuses more on high-fidelity UAV flight control. We first develop a coordination interface referred to as SimSocket for signaling exchanges between UBSim and UB-ANC in simulations, and then showcase coordinated simulations based on UBSim and UB-ANC. The new research that can be enabled by the integrated simulator is also discussed for digital twin-based UAS systems.

Original language	English (US)
Title of host publication	Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	322-327
Number of pages	6
ISBN (Electronic)	9781665495127
DOIs	https://doi.org/10.1109/DCOSS54816.2022.00059
State	Published - 2022
Externally published	Yes
Event	18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022 - Los Angeles, United States Duration: May 30 2022 → Jun 1 2022

Publication series

Name	Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022

Conference

Conference	18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022
Country/Territory	United States
City	Los Angeles
Period	5/30/22 → 6/1/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Data-Driven Control
Multi-Fidelity Simulation
UB-ANC
UBSim
Unmanned Aerial Vehicle (UAV)

Publisher link

10.1109/DCOSS54816.2022.00059

Find It

Find It at U of M Libraries

Cite this

Moorthy, S. K., Harindranath, A., McManus, M., Guan, Z., Mastronarde, N., Bentley, E. S., & Medley, M. (2022). A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC. In Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022 (pp. 322-327). (Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DCOSS54816.2022.00059

A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC. / Moorthy, Sabarish Krishna; Harindranath, Ankush; McManus, Maxwell et al.
Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 322-327 (Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Moorthy, SK, Harindranath, A, McManus, M, Guan, Z, Mastronarde, N, Bentley, ES & Medley, M 2022, A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC. in Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022. Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022, Institute of Electrical and Electronics Engineers Inc., pp. 322-327, 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022, Los Angeles, United States, 5/30/22. https://doi.org/10.1109/DCOSS54816.2022.00059

Moorthy SK, Harindranath A, McManus M, Guan Z, Mastronarde N, Bentley ES et al. A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC. In Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 322-327. (Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022). doi: 10.1109/DCOSS54816.2022.00059

Moorthy, Sabarish Krishna ; Harindranath, Ankush ; McManus, Maxwell et al. / A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC. Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 322-327 (Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022).

@inproceedings{4873ea7b478d4549a10f01f6b6410a06,

title = "A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC",

abstract = "Data-driven control based on AI/ML techniques has a great potential to enable zero-touch automated modeling, optimization and control of complex wireless systems. However, it is challenging to collect network traces in the real world because of high time and labor cost, weather limitations as well as safety concerns. In this work we attempt to tackle this challenge by designing a multi-fidelity simulator taking wireless Unmanned Aerial Vehicle (UAV) networks into consideration. We design the simulator by interfacing two Unmanned Aerial System (UAS) simulators we have developed in prior years: UBSim and UB-ANC. The former focuses on UAV network optimization and policy training by considering explicitly the network environments such as blockage dynamics, while the latter focuses more on high-fidelity UAV flight control. We first develop a coordination interface referred to as SimSocket for signaling exchanges between UBSim and UB-ANC in simulations, and then showcase coordinated simulations based on UBSim and UB-ANC. The new research that can be enabled by the integrated simulator is also discussed for digital twin-based UAS systems.",

keywords = "Data-Driven Control, Multi-Fidelity Simulation, UB-ANC, UBSim, Unmanned Aerial Vehicle (UAV)",

author = "Moorthy, \{Sabarish Krishna\} and Ankush Harindranath and Maxwell McManus and Zhangyu Guan and Nicholas Mastronarde and Bentley, \{Elizabeth Serena\} and Michael Medley",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022 ; Conference date: 30-05-2022 Through 01-06-2022",

year = "2022",

doi = "10.1109/DCOSS54816.2022.00059",

language = "English (US)",

series = "Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "322--327",

booktitle = "Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022",

}

TY - GEN

T1 - A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC

AU - Moorthy, Sabarish Krishna

AU - Harindranath, Ankush

AU - McManus, Maxwell

AU - Guan, Zhangyu

AU - Mastronarde, Nicholas

AU - Bentley, Elizabeth Serena

AU - Medley, Michael

PY - 2022

Y1 - 2022

N2 - Data-driven control based on AI/ML techniques has a great potential to enable zero-touch automated modeling, optimization and control of complex wireless systems. However, it is challenging to collect network traces in the real world because of high time and labor cost, weather limitations as well as safety concerns. In this work we attempt to tackle this challenge by designing a multi-fidelity simulator taking wireless Unmanned Aerial Vehicle (UAV) networks into consideration. We design the simulator by interfacing two Unmanned Aerial System (UAS) simulators we have developed in prior years: UBSim and UB-ANC. The former focuses on UAV network optimization and policy training by considering explicitly the network environments such as blockage dynamics, while the latter focuses more on high-fidelity UAV flight control. We first develop a coordination interface referred to as SimSocket for signaling exchanges between UBSim and UB-ANC in simulations, and then showcase coordinated simulations based on UBSim and UB-ANC. The new research that can be enabled by the integrated simulator is also discussed for digital twin-based UAS systems.

AB - Data-driven control based on AI/ML techniques has a great potential to enable zero-touch automated modeling, optimization and control of complex wireless systems. However, it is challenging to collect network traces in the real world because of high time and labor cost, weather limitations as well as safety concerns. In this work we attempt to tackle this challenge by designing a multi-fidelity simulator taking wireless Unmanned Aerial Vehicle (UAV) networks into consideration. We design the simulator by interfacing two Unmanned Aerial System (UAS) simulators we have developed in prior years: UBSim and UB-ANC. The former focuses on UAV network optimization and policy training by considering explicitly the network environments such as blockage dynamics, while the latter focuses more on high-fidelity UAV flight control. We first develop a coordination interface referred to as SimSocket for signaling exchanges between UBSim and UB-ANC in simulations, and then showcase coordinated simulations based on UBSim and UB-ANC. The new research that can be enabled by the integrated simulator is also discussed for digital twin-based UAS systems.

KW - Data-Driven Control

KW - Multi-Fidelity Simulation

KW - UB-ANC

KW - UBSim

KW - Unmanned Aerial Vehicle (UAV)

UR - https://www.scopus.com/pages/publications/85139438927

UR - https://www.scopus.com/inward/citedby.url?scp=85139438927&partnerID=8YFLogxK

U2 - 10.1109/DCOSS54816.2022.00059

DO - 10.1109/DCOSS54816.2022.00059

M3 - Conference contribution

AN - SCOPUS:85139438927

T3 - Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022

SP - 322

EP - 327

BT - Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022

Y2 - 30 May 2022 through 1 June 2022

ER -

A Middleware for Digital Twin-Enabled Flying Network Simulations Using UBSim and UB-ANC

Abstract

Publication series

Conference

Bibliographical note

Keywords

Publisher link

Find It

Other files and links

Fingerprint

Cite this