Dynamic Load Balancing Framework for Compute-Network Resource Integration in MEC-Assisted Autonomous Vehicles

Jeonghwan Kim; Juho Song; Hoonsung Chwa; Ji Woong Choi; Jeongho Kwak

doi:10.1109/ICUFN65838.2025.11170057

Dynamic Load Balancing Framework for Compute-Network Resource Integration in MEC-Assisted Autonomous Vehicles

Jeonghwan Kim
, Juho Song
, Hoonsung Chwa
, Ji Woong Choi
, 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

As autonomous driving technology becomes more advanced, vehicle-edge computing (VEC) has drawn significant attention. However, it still faces challenges due to varying network conditions and the availability of roadside units (RSUs). In this paper, we present a Lyapunov optimization-based algorithm that jointly optimizes offloading decisions and computing resources, aiming to reduce energy consumption while keeping service time within acceptable limits through both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. We then evaluate the real-world performance of this algorithm by using simulator, which integrates a network model, an in-vehicle processing model in MATLAB, a vehicle topology model, and realistic driving scenarios generated with a virtual test drive (VTD).

Original language	English
Title of host publication	ICUFN 2025 - 16th International Conference on Ubiquitous and Future Networks
Publisher	IEEE Computer Society
Pages	6-8
Number of pages	3
ISBN (Electronic)	9798331524876
DOIs	https://doi.org/10.1109/ICUFN65838.2025.11170057
State	Published - 2025
Event	16th International Conference on Ubiquitous and Future Networks, ICUFN 2025 - Hybrid, Lisbon, Portugal Duration: 8 Jul 2025 → 11 Jul 2025

Publication series

Name	International Conference on Ubiquitous and Future Networks, ICUFN
ISSN (Print)	2165-8528
ISSN (Electronic)	2165-8536

Conference

Conference	16th International Conference on Ubiquitous and Future Networks, ICUFN 2025
Country/Territory	Portugal
City	Hybrid, Lisbon
Period	8/07/25 → 11/07/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

autonomous vehicle
load balancing
Lyapunov optimization
task offloading
VTD simulator

UN SDGs

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

Access to Document

10.1109/ICUFN65838.2025.11170057

Cite this

Kim, J., Song, J., Chwa, H., Choi, J. W., & Kwak, J. (2025). Dynamic Load Balancing Framework for Compute-Network Resource Integration in MEC-Assisted Autonomous Vehicles. In ICUFN 2025 - 16th International Conference on Ubiquitous and Future Networks (pp. 6-8). (International Conference on Ubiquitous and Future Networks, ICUFN). IEEE Computer Society. https://doi.org/10.1109/ICUFN65838.2025.11170057

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title = "Dynamic Load Balancing Framework for Compute-Network Resource Integration in MEC-Assisted Autonomous Vehicles",

abstract = "As autonomous driving technology becomes more advanced, vehicle-edge computing (VEC) has drawn significant attention. However, it still faces challenges due to varying network conditions and the availability of roadside units (RSUs). In this paper, we present a Lyapunov optimization-based algorithm that jointly optimizes offloading decisions and computing resources, aiming to reduce energy consumption while keeping service time within acceptable limits through both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. We then evaluate the real-world performance of this algorithm by using simulator, which integrates a network model, an in-vehicle processing model in MATLAB, a vehicle topology model, and realistic driving scenarios generated with a virtual test drive (VTD).",

keywords = "autonomous vehicle, load balancing, Lyapunov optimization, task offloading, VTD simulator",

author = "Jeonghwan Kim and Juho Song and Hoonsung Chwa and Choi, \{Ji Woong\} and Jeongho Kwak",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 16th International Conference on Ubiquitous and Future Networks, ICUFN 2025 ; Conference date: 08-07-2025 Through 11-07-2025",

year = "2025",

doi = "10.1109/ICUFN65838.2025.11170057",

language = "English",

series = "International Conference on Ubiquitous and Future Networks, ICUFN",

publisher = "IEEE Computer Society",

pages = "6--8",

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}

Kim, J, Song, J, Chwa, H , Choi, JW & Kwak, J 2025, Dynamic Load Balancing Framework for Compute-Network Resource Integration in MEC-Assisted Autonomous Vehicles. in ICUFN 2025 - 16th International Conference on Ubiquitous and Future Networks. International Conference on Ubiquitous and Future Networks, ICUFN, IEEE Computer Society, pp. 6-8, 16th International Conference on Ubiquitous and Future Networks, ICUFN 2025, Hybrid, Lisbon, Portugal, 8/07/25. https://doi.org/10.1109/ICUFN65838.2025.11170057

Dynamic Load Balancing Framework for Compute-Network Resource Integration in MEC-Assisted Autonomous Vehicles. / Kim, Jeonghwan; Song, Juho; Chwa, Hoonsung et al.
ICUFN 2025 - 16th International Conference on Ubiquitous and Future Networks. IEEE Computer Society, 2025. p. 6-8 (International Conference on Ubiquitous and Future Networks, ICUFN).

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

TY - GEN

T1 - Dynamic Load Balancing Framework for Compute-Network Resource Integration in MEC-Assisted Autonomous Vehicles

AU - Kim, Jeonghwan

AU - Song, Juho

AU - Chwa, Hoonsung

AU - Choi, Ji Woong

AU - Kwak, Jeongho

PY - 2025

Y1 - 2025

N2 - As autonomous driving technology becomes more advanced, vehicle-edge computing (VEC) has drawn significant attention. However, it still faces challenges due to varying network conditions and the availability of roadside units (RSUs). In this paper, we present a Lyapunov optimization-based algorithm that jointly optimizes offloading decisions and computing resources, aiming to reduce energy consumption while keeping service time within acceptable limits through both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. We then evaluate the real-world performance of this algorithm by using simulator, which integrates a network model, an in-vehicle processing model in MATLAB, a vehicle topology model, and realistic driving scenarios generated with a virtual test drive (VTD).

AB - As autonomous driving technology becomes more advanced, vehicle-edge computing (VEC) has drawn significant attention. However, it still faces challenges due to varying network conditions and the availability of roadside units (RSUs). In this paper, we present a Lyapunov optimization-based algorithm that jointly optimizes offloading decisions and computing resources, aiming to reduce energy consumption while keeping service time within acceptable limits through both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. We then evaluate the real-world performance of this algorithm by using simulator, which integrates a network model, an in-vehicle processing model in MATLAB, a vehicle topology model, and realistic driving scenarios generated with a virtual test drive (VTD).

KW - autonomous vehicle

KW - load balancing

KW - Lyapunov optimization

KW - task offloading

KW - VTD simulator

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U2 - 10.1109/ICUFN65838.2025.11170057

DO - 10.1109/ICUFN65838.2025.11170057

M3 - Conference contribution

AN - SCOPUS:105018743658

T3 - International Conference on Ubiquitous and Future Networks, ICUFN

SP - 6

EP - 8

BT - ICUFN 2025 - 16th International Conference on Ubiquitous and Future Networks

PB - IEEE Computer Society

T2 - 16th International Conference on Ubiquitous and Future Networks, ICUFN 2025

Y2 - 8 July 2025 through 11 July 2025

ER -

Kim J, Song J, Chwa H , Choi JW , Kwak J. Dynamic Load Balancing Framework for Compute-Network Resource Integration in MEC-Assisted Autonomous Vehicles. In ICUFN 2025 - 16th International Conference on Ubiquitous and Future Networks. IEEE Computer Society. 2025. p. 6-8. (International Conference on Ubiquitous and Future Networks, ICUFN). doi: 10.1109/ICUFN65838.2025.11170057

Dynamic Load Balancing Framework for Compute-Network Resource Integration in MEC-Assisted Autonomous Vehicles

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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