PE-MHMR: Energy-Efficient Multi-Hop Route Prediction for Data Offloading in Vehicular Networks
Abstract
Vehicular Ad-Hoc Networks (VANETs) and Intelligent Transportation Systems (ITS) have experienced remarkable developments in the last years. Finding the optimal route for data offloading from vehicles can ensure the effectiveness of ITSs and the network. This work presents the Predicted Energetic Multi-hop Multi-RSU (PE-MHMR) for data offloading in VANETS, considering multiple hops in RSU (Radio Side Units) overlapping scenarios. It is based on an efficient transfer from the source node to the destination node, by finding the shortest and most energy-efficient path. Complex networks were used to calculate the links probability success. Shorter, more energy-efficient and more successful routes are sought by the PE-MHMR algorithm. The metrics used to evaluate the algorithm were data loss, offloading fraction and successful offloading fraction. The simulation results demonstrate that more efficient routes can be calculated using PE-MHMR.
Keywords:
Intelligent Transportation Systems, Vehicular Networks, Data Offloading
References
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Wisitpongphan, N., Tonguz, O. K., Parikh, J. S., Mudalige, P., Bai, F., and Sadekar, V. (2007). Broadcast storm mitigation techniques in vehicular ad hoc networks. IEEE Wireless Communications, 14(6), 84–94.
Zeng, F., Zhang, Z., and Wu, J. (2024). Task offloading delay minimization in vehicular edge computing based on vehicle trajectory prediction. Digital Communications and Networks.
Zhu, H., Liu, J., Jin, L., and Zhang, G. (2023). Intersection-based unicast routing using ant colony optimization in software-defined vehicular networks. Electronics, 12(7), 1620.
Choi, Y. and Lim, Y. (2023). Deep reinforcement learning for edge caching with mobility prediction in vehicular networks. Sensors, 23(3), 1732.
Da-Silva, L. S., Storck, C. R., and de LP Duarte-Figueiredo, F. (2019). A dynamic load balancing algorithm for data plane traffic. In IEEE Latin American Network Operations and Management Symposium, LANOMS.
Dai, W. (2023). Joint task offloading, resource allocation and data caching in MEC-assisted vehicular network. In 2023 4th International Conference on Computer Engineering and Application (ICCEA), pages 70–76. IEEE.
Duarte-Figueiredo, F. and Loureiro, A. A. F. (2004). DiffMobil – Uma Arquitetura de Qualidade de Serviço Fim-a-Fim em Redes GPRS. PhD thesis, UFMG.
Feng, C., Han, P., Zhang, X., Yang, B., Liu, Y., and Guo, L. (2022). Computation offloading in mobile edge computing networks: A survey. Journal of Network and Computer Applications, 202, 103366.
Hassan, S.-U., Shabbir, M., Iqbal, S., Said, A., Kamiran, F., Nawaz, R., and Saif, U. (2021). Leveraging deep learning and SNA approaches for smart city policing in the developing world. International Journal of Information Management, 56, 102045.
Huang, C.-M. and Lai, C.-F. (2020). The delay-constrained and network-situation-aware V2V2I VANET data offloading based on the multi-access edge computing (MEC) architecture. IEEE Open Journal of Vehicular Technology, 1, 331–347.
Huang, C.-M., Lin, S.-Y., and Wu, Z.-Y. (2020). The k-hop-limited V2V2I VANET data offloading using the mobile edge computing (MEC) mechanism. Vehicular Communications, 26, 100268.
Hussein, A. A. and Mahmood, D. A. (2023). Connectivity analysis in vehicular ad-hoc network based on VDTN. Journal of Communications Software and Systems, 19(2), 147–157.
Islam, M. M., Newaz, A. A. R., Song, L., Lartey, B., Lin, S.-C., Fan, W., Hajbabaie, A., Khan, M. M., Partovi, A., Phuapaiboon, T., et al. (2023). Connected autonomous vehicles: State of practice. Applied Stochastic Models in Business and Industry, 39(5), 684–700.
Lin, S.-Y., Huang, C.-M., and Wu, T.-Y. (2022). Multi-access edge computing-based vehicle-vehicle-RSU data offloading over the multi-RSU-overlapped environment. IEEE Open Journal of Intelligent Transportation Systems, 3, 7–32.
Lousada, E. E. and Duarte-Figueiredo, F. (2024). Uma abordagem para offloading em redes veiculares considerando múltiplos saltos em um cenário de sobreposição de RSUs. PhD thesis, PUC Minas.
Lousada, E. E., Storck, C. R., Mini, R. A., and Duarte-Figueiredo, F. d. L. P. (2019). Using complex networks metrics to mitigate the broadcast storm problem. In 2019 IEEE Symposium on Computers and Communications (ISCC), pages 1–6. IEEE.
Lousada, E. E. d. O. and Figueiredo, F. d. L. P. D. (2024a). An approach for offloading with multi-hop considerations in an RSU signal overlay setting. Revista de Gestão e Secretariado, 15(4), e3739.
Lousada, E. E. d. O. and Figueiredo, F. d. L. P. D. (2024b). CN-FFVP: Uma solução para mitigação de tempestade de broadcast baseada em métricas de redes complexas, distância e energia dos nós. Observatório de la Economía Latinoamericana, 22(1), 4494–4512.
Rashid, S. A., Audah, L., Hamdi, M. M., Abdulsattar, N. F., Mutar, M. H., and Alkhafaji, M. A. (2023). Centralized RSU deployment strategy for effective communication in multi-hop vehicular ad-hoc networks (VANETs). In International Conference on Innovative Computing and Communication, pages 53–65. Springer.
Song, X., Wang, Y., Xie, Z., Zhang, R., and Xu, S. (2023a). Dingo-optimization-based task-offloading algorithm in multihop V2V/V2I-enabled networks. Transactions on Emerging Telecommunications Technologies, 34(9), e4823.
Song, X., Zhang, R., Wang, Y., Yu, Y., and Xu, S. (2023b). Incentive mechanism design for two-layer mobile data offloading networks: A contract theory approach. Ad Hoc Networks, 144, 103154.
Wang, L. (2024). VANET toolbox: A vehicular network simulator based on discrete event simulation. MATLAB Central File Exchange.
Wang, P., Wang, Y., Qiao, J., and Hu, Z. (2023). Traffic-aware optimization of task offloading and content caching in the Internet of Vehicles. Applied Sciences, 13(24), 13069.
Wisitpongphan, N., Tonguz, O. K., Parikh, J. S., Mudalige, P., Bai, F., and Sadekar, V. (2007). Broadcast storm mitigation techniques in vehicular ad hoc networks. IEEE Wireless Communications, 14(6), 84–94.
Zeng, F., Zhang, Z., and Wu, J. (2024). Task offloading delay minimization in vehicular edge computing based on vehicle trajectory prediction. Digital Communications and Networks.
Zhu, H., Liu, J., Jin, L., and Zhang, G. (2023). Intersection-based unicast routing using ant colony optimization in software-defined vehicular networks. Electronics, 12(7), 1620.
Published
2025-05-19
How to Cite
LOUSADA, Efrem Eladie de Oliveira; DUARTE-FIGUEIREDO, Fátima.
PE-MHMR: Energy-Efficient Multi-Hop Route Prediction for Data Offloading in Vehicular Networks. In: URBAN COMPUTING WORKSHOP (COURB), 9. , 2025, Natal/RN.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 141-154.
ISSN 2595-2706.
DOI: https://doi.org/10.5753/courb.2025.8893.
