Abstract
The emerging Vehicle to Infrastructure (V2I) technology supports the service of task offloading under the Internet of vehicle (IoV), which improves the computational efficiency of the task. Facing tasks with different demands, network slicing technology builds a variety of logic private networks on a unified infrastructure, divides and allocates resources according to different user needs, which improves the vehicle transmission efficiency. Nevertheless, the diversity of demand resources and the randomness of tasks make the network scenario of IoV more complex. It is still a challenge to consider how to combine the network slicing technology to reduce the cost of offloading the computing task. In this paper, we study the scenario of autonomous vehicle offloading the computing task to Roadside Units (RSUs), and consider the multi-Mobile Edge Computing (multi-MEC) collaborative computing task to ensure that the task can be completed within tolerable delay. We consider the computing power and resource occupancy rate of MEC servers to ensure the user experience, and formulate a resource pricing scheme. Then, we propose a Performance-Price Ratio Task Scheduling (PPRTS) algorithm, which aims to complete the computing task within the maximum tolerable delay and reduce the cost of user. Simulation results show that the algorithm can effectively reduce the cost of the user.
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Acknowledgement
This work is partly supported by the National Natural Science Foundation of China (Nos. 61872044, 61902029), The Key Research and Cultivation Projects at Beijing Information Science and Technology University (No. 5211823411).
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Liang, Y., Chen, X., Ma, S., Jiao, L. (2021). Delay-Sensitive Slicing Resources Scheduling Based on Multi-MEC Collaboration in IoV. In: Gao, H., Wang, X. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 407. Springer, Cham. https://doi.org/10.1007/978-3-030-92638-0_4
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DOI: https://doi.org/10.1007/978-3-030-92638-0_4
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