Abstract
With the rapid development of the Internet of Vehicles (IoV), various types of compute-intensive vehicle applications are emerging and present significant challenges to resource-constrained vehicles. Emerging vehicular edge computing (VEC) can alleviate this situation by offloading computational tasks from vehicles to base stations (BSs) with edge servers at the roadside. And the excellent transmission performance of 5G provides more reliable support for VEC. However, due to the drawbacks of small coverage area and high energy cost of 5G BSs, long-term usage will result in huge costly resource investment. In this paper, we design a new 4G–5G hybrid task offloading framework for the VEC scenario. We consider switching some of the 5G BSs to sleep state during low traffic and low data consumption conditions, while letting the 4G BS process the tasks generated in these areas. We first build the mathematical model and find that it cannot be solved directly. Then we design the algorithm for the offline case and the online case, respectively. Simulation results show that our scheme significantly reduces the energy cost while ensuring high task success rate.
The work is supported by the major science and technology projects in Anhui Province, Grant No. 202003a05020009 and innovation foundation of the city of Bengbu, Grant No. JZ2022YDZJ0019.
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Zhao, F., Shi, L., Shi, Y., Zhao, S., Lv, Z. (2022). An Energy-Saving Strategy for 5G Base Stations in Vehicular Edge Computing. In: Gao, H., Wang, X., Wei, W., Dagiuklas, T. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 460 . Springer, Cham. https://doi.org/10.1007/978-3-031-24383-7_17
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