Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture

Pyeongjun Choi; Pildo Yoon; Jeongho Kwak

doi:10.1109/ICTC58733.2023.10392945

Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture

Pyeongjun Choi
, Pildo Yoon
, Jeongho Kwak

Department of Electrical Engineering and Computer Science

Daegu Gyeongbuk Institute of Science and Technology

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

Abstract

Advanced autonomous driving services at Level 4 and above eliminate the need for constant driver supervision, enabling vehicles to respond autonomously to various driving scenarios. The integration of components under edge environment such as the On Board Unit (OBU), Road Side Units (RSUs), and cloud infrastructure, facilitated by V2X communication, enhances perception, decision-making, and control capabilities. However, existing standards lack guidance on efficient computing resource management in autonomous driving systems. To address this, we propose a dynamic computing load balancing algorithm for the cloud-RSU-vehicle architecture. This algorithm optimizes resource allocation and utilization, considering network conditions, computational capabilities, and processing queues using Lyapunov optimization techniques. The stability of the algorithm and trade-off between processing delay and energy consumption is inspected through simulation.

Original language	English
Title of host publication	ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence
Subtitle of host publication	Exploring the Frontiers of ICT Innovation
Publisher	IEEE Computer Society
Pages	737-739
Number of pages	3
ISBN (Electronic)	9798350313277
DOIs	https://doi.org/10.1109/ICTC58733.2023.10392945
State	Published - 2023
Event	14th International Conference on Information and Communication Technology Convergence, ICTC 2023 - Jeju Island, Korea, Republic of Duration: 11 Oct 2023 → 13 Oct 2023

Publication series

Name	International Conference on ICT Convergence
ISSN (Print)	2162-1233
ISSN (Electronic)	2162-1241

Conference

Conference	14th International Conference on Information and Communication Technology Convergence, ICTC 2023
Country/Territory	Korea, Republic of
City	Jeju Island
Period	11/10/23 → 13/10/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Edge computing
Load balancing
Lyapunov optimization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICTC58733.2023.10392945

Cite this

Choi, P., Yoon, P., & Kwak, J. (2023). Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture. In ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation (pp. 737-739). (International Conference on ICT Convergence). IEEE Computer Society. https://doi.org/10.1109/ICTC58733.2023.10392945

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title = "Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture",

abstract = "Advanced autonomous driving services at Level 4 and above eliminate the need for constant driver supervision, enabling vehicles to respond autonomously to various driving scenarios. The integration of components under edge environment such as the On Board Unit (OBU), Road Side Units (RSUs), and cloud infrastructure, facilitated by V2X communication, enhances perception, decision-making, and control capabilities. However, existing standards lack guidance on efficient computing resource management in autonomous driving systems. To address this, we propose a dynamic computing load balancing algorithm for the cloud-RSU-vehicle architecture. This algorithm optimizes resource allocation and utilization, considering network conditions, computational capabilities, and processing queues using Lyapunov optimization techniques. The stability of the algorithm and trade-off between processing delay and energy consumption is inspected through simulation.",

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Choi, P, Yoon, P & Kwak, J 2023, Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture. in ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation. International Conference on ICT Convergence, IEEE Computer Society, pp. 737-739, 14th International Conference on Information and Communication Technology Convergence, ICTC 2023, Jeju Island, Korea, Republic of, 11/10/23. https://doi.org/10.1109/ICTC58733.2023.10392945

Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture. / Choi, Pyeongjun; Yoon, Pildo; Kwak, Jeongho.
ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation. IEEE Computer Society, 2023. p. 737-739 (International Conference on ICT Convergence).

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

TY - GEN

T1 - Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture

AU - Choi, Pyeongjun

AU - Yoon, Pildo

AU - Kwak, Jeongho

PY - 2023

Y1 - 2023

N2 - Advanced autonomous driving services at Level 4 and above eliminate the need for constant driver supervision, enabling vehicles to respond autonomously to various driving scenarios. The integration of components under edge environment such as the On Board Unit (OBU), Road Side Units (RSUs), and cloud infrastructure, facilitated by V2X communication, enhances perception, decision-making, and control capabilities. However, existing standards lack guidance on efficient computing resource management in autonomous driving systems. To address this, we propose a dynamic computing load balancing algorithm for the cloud-RSU-vehicle architecture. This algorithm optimizes resource allocation and utilization, considering network conditions, computational capabilities, and processing queues using Lyapunov optimization techniques. The stability of the algorithm and trade-off between processing delay and energy consumption is inspected through simulation.

AB - Advanced autonomous driving services at Level 4 and above eliminate the need for constant driver supervision, enabling vehicles to respond autonomously to various driving scenarios. The integration of components under edge environment such as the On Board Unit (OBU), Road Side Units (RSUs), and cloud infrastructure, facilitated by V2X communication, enhances perception, decision-making, and control capabilities. However, existing standards lack guidance on efficient computing resource management in autonomous driving systems. To address this, we propose a dynamic computing load balancing algorithm for the cloud-RSU-vehicle architecture. This algorithm optimizes resource allocation and utilization, considering network conditions, computational capabilities, and processing queues using Lyapunov optimization techniques. The stability of the algorithm and trade-off between processing delay and energy consumption is inspected through simulation.

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KW - Lyapunov optimization

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DO - 10.1109/ICTC58733.2023.10392945

M3 - Conference contribution

AN - SCOPUS:85184582535

T3 - International Conference on ICT Convergence

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BT - ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence

PB - IEEE Computer Society

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Y2 - 11 October 2023 through 13 October 2023

ER -

Choi P, Yoon P, Kwak J. Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture. In ICTC 2023 - 14th International Conference on Information and Communication Technology Convergence: Exploring the Frontiers of ICT Innovation. IEEE Computer Society. 2023. p. 737-739. (International Conference on ICT Convergence). doi: 10.1109/ICTC58733.2023.10392945

Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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