Skip to main content
SpringerLink
Log in

Parked vehicles crowdsourcing for task offloading in vehicular edge computing

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

With computation offloading widely used in the computation-intensive vehicular applications, vehicular edge computing (VEC) faces the resource shortage of VEC servers. In this paper, the idle resources in the parked vehicles are aggregated to process the offloaded computing tasks, and the incentive schemes are proposed to encourage the parked vehicles to make the contribution to VEC. First, we propose a system architecture for task offloading, in which the edge crowdsourcing platform (ECP) is designed to manage and schedule the resources of parked vehicles for VEC, and a requesting vehicle can offload the computing tasks to the VEC server and the ECP simultaneously. Then, based on the Stackelberg game, we formulate the interactions between the participants of VEC as a task allocation optimization problem and establish a price model in which each participant can obtain their maximum utilities. Finally, we theoretically prove the existence and uniqueness of the Stackelberg equilibrium in this game, and a gradient iterative algorithm is proposed to determine the task allocation between the VEC server and the ECP, meanwhile achieving their best strategies. The simulation results demonstrate that the performance of the proposed scheme is better than that of traditional methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Data availibility statement

Not applicable.

References

  1. Foh CH, Kantarci B, Chatzimisios P, Wu J, Gao D (2016) IEEE Access Special Section Editorial: Advances in Vehicular Clouds. IEEE Access 4:10315–10317. https://doi.org/10.1109/ACCESS.2017.2652283

    Article  Google Scholar 

  2. Sharma MK, Kaur A (2015) A Survey on Vehicular Cloud Computing and Its Security. In 2015 1st International Conference on Next Generation Computing Technologies (NGCT), Dehradun, pp 67-71. https://doi.org/10.1109/NGCT.2015.7375084

  3. Cheng X, Chen C, Zhang W, Yang Y (2017) 5G-Enabled Cooperative Intelligent Vehicular (5GenCIV) Framework: When Benz Meets Marconi. IEEE Intell Syst 32(3):53–59. https://doi.org/10.1109/MIS.2017.53

    Article  Google Scholar 

  4. Cheng X, Zhang R, Yang L (2019) Wireless Toward the Era of Intelligent Vehicles. IEEE Internet Things J 6(1):188–202. https://doi.org/10.1109/JIOT.2018.2884200

    Article  Google Scholar 

  5. Mao Y, You C, Zhang J, Huang K, Letaief KB (2017) A Survey on Mobile Edge Computing: The Communication Perspective. IEEE Commun Surv Tutorials 19(4):2322–2358. https://doi.org/10.1109/COMST.2017.2745201

    Article  Google Scholar 

  6. Ahmed A, Ahmed E (2016) A Survey on Mobile Edge Computing. In 2016 10th International Conference on Intelligent Systems and Control (ISCO), Coimbatore, pp 1-8. https://doi.org/10.1109/ISCO.2016.7727082

  7. Zhang K, Mao Y, Leng S et al (2016) Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks. IEEE Access 4:5896–5907. https://doi.org/10.1109/ACCESS.2016.2597169

    Article  Google Scholar 

  8. Guo H, Liu J (2018) Collaborative Computation Offloading for Multiaccess Edge Computing Over Fiber-Wireless Networks. IEEE Trans Veh Technol 67(5):4514–4526. https://doi.org/10.1109/TVT.2018.2790421

    Article  Google Scholar 

  9. Zhang K, Mao Y, Leng S, Maharjan S, Zhang Y (2017) Optimal Delay Constrained Offloading for Vehicular Edge Computing Networks. In 2017 IEEE International Conference on Communications (ICC), Paris, pp 1-6. https://doi.org/10.1109/ICC.2017.7997360

  10. Huang X, Yu R, Liu J et al (2018) Parked Vehicle Edge Computing: Exploiting Opportunistic Resources for Distributed Mobile Applications. IEEE Access 6:66649–66663

    Article  Google Scholar 

  11. Zhou S, Xu Q, Hui Y et al (2016) A Game Theoretic Approach to Parked Vehicle Assisted Content Delivery in Vehicular Ad Hoc Networks. IEEE Trans Veh Technol 66(7):6461–64742016

    Google Scholar 

  12. Han D, Chen W, Fang Y (2019) A Dynamic Pricing Strategy for Vehicle Assisted Mobile Edge Computing Systems. IEEE Wireless Commun Lett 8(2):420–423

    Article  Google Scholar 

  13. Salahuddin MA, Al-Fuqaha A, Guizani M (2016) Reinforcement Learning for Resource Provisioning in the Vehicular Cloud. IEEE Wirel Commun 23(4):128–135

    Article  Google Scholar 

  14. Zhang L, Zhao Z, Wu Q, Zhao H, Xu H, Wu X (2018) Energy-Aware Dynamic Resource Allocation in UAV Assisted Mobile Edge Computing Over Social Internet of Vehicles. IEEE Access 6:56700–56715. https://doi.org/10.1109/ACCESS.2018.2872753

    Article  Google Scholar 

  15. Qiao G, Leng S, Zhang K, He Y (2018) Collaborative Task Offloading in Vehicular Edge Multi-Access Networks. IEEE Commun Mag 56(8):48–54. https://doi.org/10.1109/MCOM.2018.1701130

    Article  Google Scholar 

  16. Huang X, Yu R, Kang J, He Y, Zhang Y (2017) Exploring Mobile Edge Computing for 5G-Enabled Software Defined Vehicular Networks. IEEE Wirel Commun 24(6):55–63. https://doi.org/10.1109/MWC.2017.1600387

    Article  Google Scholar 

  17. Zeng F, Chen Q, Meng L, Wu J (2021) Volunteer Assisted Collaborative Offloading and Resource Allocation in Vehicular Edge Computing. IEEE Trans Intell Transp Syst 22(6):3247–3257

    Article  Google Scholar 

  18. Aloqaily M, Kantarci B, Mouftah HT (2016) Multiagent/Multiobjective Interaction Game System for Service Provisioning in Vehicular Cloud. IEEE Access 4:3153–3168. https://doi.org/10.1109/ACCESS.2016.2575038

    Article  Google Scholar 

  19. Zeng F, Chen Y, Yao L, Wu J (2021) A Novel Reputation Incentive Mechanism and Game Theory Analysis for Service Caching in Software-Defined Vehicle Edge Computing. Peer-to-Peer Networking and Applications 14(2):467–481

    Article  Google Scholar 

  20. Wang R, Zeng F, Deng X, Wu J (2021) Joint Computation Offloading and Resource Allocation in Vehicular Edge Computing Based on An Economic Theory: Walrasian Equilibrium. Peer-to-Peer Networking and Applications 14(6):3971–3983

    Article  Google Scholar 

  21. Zhang Z, Zeng F (2023) Efficient Task Allocation for Computation Offloading in Vehicular Edge Computing. IEEE Internet Things J 10(6):5595–5606

    Article  Google Scholar 

  22. Wang R, Zeng F, Yao L, Wu J (2020) Game-Theoretic Algorithm Designs and Analysis for Interactions among Contributors in Mobile Crowdsourcing with Word of Mouth. IEEE Internet Things J 7(9):8271–8286

    Article  Google Scholar 

  23. Zeng F, Zhang K, Wu L, Wu J (2023) Efficient Caching in Vehicular Edge Computing Based on Edge-Cloud Collaboration. IEEE Trans Veh Technol 72(2):2468–2481

    Article  Google Scholar 

  24. Zhang H, Xiao Y, Bu S, Niyato D, Yu FR, Han Z (2017) Computing Resource Allocation in Three-Tier IoT Fog Networks: A Joint Optimization Approach Combining Stackelberg Game and Matching. IEEE Internet Things J 4(5):1204–1215. https://doi.org/10.1109/JIOT.2017.2688925

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the anonymous reviewers for their constructive comments.

Funding

This work is supported in part by the National Science Foundation of China (Grant No. 62172450), the Key R &D Plan of Hunan Province (Grant No. 2022GK2008) and the Nature Science Foundation of Hunan Province (Grant No. 2020JJ4756).

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Main Campus of Central South University, Lushan South Road No. 932, Changsha, 410083, China

    Feng Zeng, Ranran Rou & Qi Deng

  2. Department of Computer Science, Universidad de Chile, Santiago, Chile

    Jinsong Wu

Authors
  1. Feng Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ranran Rou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qi Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jinsong Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

F. Z. conceived and designed the experiments, R. R. performed the experiments, R. R. and Q. D. analyzed the data, and F.Z. and J. W. wrote the main manuscript text. All authors reviewed the manuscript.

Corresponding author

Correspondence to Feng Zeng.

Ethics declarations

Ethics approval

Not applicable.

Consent to publish

Not applicable.

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection: 1- Track on Networking and Application

Guest Editor: Vojislav B. Misic

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zeng, F., Rou, R., Deng, Q. et al. Parked vehicles crowdsourcing for task offloading in vehicular edge computing. Peer-to-Peer Netw. Appl. 16, 1803–1818 (2023). https://doi.org/10.1007/s12083-023-01496-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-023-01496-8

Keywords

Search

Navigation