Abstract
In the future intelligent transportation system (ITSs), there will be a lot of negotiation work between vehicle and vehicle (V2V) and between vehicle and infrastructure (V2I), so it is very necessary to design efficient and energy-saving offloading strategy. Aiming at the three conflicting optimization objectives of offloading delay, energy consumption and load balancing, an efficient and energy-saving offloading decision scheme in the scenario of Internet of vehicles was proposed in this paper. Firstly, the task segmentation model, offloading delay model, energy consumption model, load balancing model and multi-objective optimization model were constructed. Then, based on the comprehensive consideration of data offloading delay, energy consumption and load balance, a task offloading scheme based on MOEA/D was proposed. Finally, the proposed scheme was compared with NSGA-II-based scheme, NSGA-III-based scheme,PESA-II-based scheme and SPEA-II-based scheme. The simulation results show that a task offloading scheme based on MOEA/D is obviously superior to the above schemes in terms of offloading delay, energy consumption and load balancing, and can provide efficient and energy-saving offloading service.












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Data Availability
The datasets generated during and analysed during the current study are not publicly available due to [REASON(S) WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.
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Funding
This project was supported by Tianjin Natural Science Foundation General Project (22JCZDJC00600).
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by ZHU Si-feng, WANG Yu, CHEN Hao and Zhang Hui. The first draft of the manuscript was written by WANG Yu and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Zhu, Sf., Wang, Y., Chen, H. et al. A Novel Internet of Vehicles’s Task Offloading Decision Optimization Scheme for Intelligent Transportation System. Wireless Pers Commun 137, 2359–2379 (2024). https://doi.org/10.1007/s11277-024-11499-0
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DOI: https://doi.org/10.1007/s11277-024-11499-0