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Relay-Assisted Task Offloading Optimization for MEC-Enabled Internet of Vehicles

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Abstract

Mobile edge computing (MEC)-enabled Internet of Vehicles (IoV) is a promising way to provide low latency and high computation functions to smart vehicles. Owing to the mobility of vehicles and unpredicted distribution of computation-intensive tasks, computational resources at the edge may be utilized with only low efficiency. To solve this problem, this study investigates a relay-supported task offloading scheme in MEC-enabled IoV. In this scheme, computational tasks produced by vehicles are predictively offloaded to MEC nodes through relays to improve the allocation of computational resources. A combinational problem is used to model relay selection for vehicles connected to the MEC. To solve the corresponding problem, a low-complexity algorithm that combines the Hungarian and the Greedy algorithms is designed. Simulation results show that the proposed scheme achieves better performance than existing schemes in terms of overall efficiency and offloading time.

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References

  1. Ma, M., He, D., Wang, H., Kumar, N., Choo, K.R.: An efficient and provably secure authenticated key agreement protocol for fog-based vehicular ad-hoc networks. IEEE Internet Things J. 6(5), 8065–8075 (2019)

    Article  Google Scholar 

  2. Zhang, K.,Mao, Y., Leng, Y., He, Y., Zhang, Y.: Mobile-edge computing for vehicular networks: a promising network paradigm with predictive off-loading. IEEE Veh. Technol. Mag. 12(2),36–44 (2017)

    Google Scholar 

  3. Zheng, C., Feng, D., Zhang, S., Xia, X., Qian, G., Li, G.Y.: Energy efficient V2X-enabled communications in cellular networks. IEEE Trans. Veh. Technol. 68(1), 554–564 (2019)

    Article  Google Scholar 

  4. Tran, T.X., Hajisami, A., Pandey, P., Pompili, D.: Collaborative mobile edge computing in 5g networks: new paradigms, scenarios, and challenges. IEEE Commun. Mag. 55(4), 54–61 (2017)

    Article  Google Scholar 

  5. Porambage, P., Okwuibe, J., Liyanage, M., Ylianttila, M., Taleb, T.: Survey on multi-access edge computing for internet of things realization. IEEE Commun. Surv. Tutor. 20(4), 2961–2991, Fourthquarter 2018

    Google Scholar 

  6. Yang, C., Liu, Y., Chen, X., Zhong, W., Xie, S.: Efficient mobility-aware task offloading for vehicular edge computing networks. IEEE Access 7, 26652–26664 (2019)

    Article  Google Scholar 

  7. Moltchanov, D., Kovalchukov, R., Gerasimenko, M., Andreev, S., Koucheryavy, Y., Gerla, M.: Socially inspired relaying and proactive mode selection in mmWave vehicular communications. IEEE Internet Things J. 6(3), 5172–5183 (2019)

    Article  Google Scholar 

  8. Feng, J., Liu, Z., Wu, C., Ji, Y.: Mobile edge computing for the internet of vehicles: offloading framework and job scheduling. IEEE Veh. Technol. Mag. 14(1), 28–36 (2019)

    Article  Google Scholar 

  9. Cao, X., Wang, F., Xu, J., Zhang, R., Cui, S.: Joint computation and communication cooperation for energy-efficient mobile edge computing. IEEE Internet Things J. 6(3), 4188–4200 (2019)

    Article  Google Scholar 

  10. Wang, Z., Zhong, Z., Zhao, D., Ni, M.: Vehicle-based cloudlet relaying for mobile computation offloading. IEEE Trans. Veh. Technol. 67(11), 11181–11191 (2018)

    Article  Google Scholar 

  11. Luoto, P., Bennis, M., Pirinen, P., Samarakoon, S., Horneman, K., Latva-aho, M.: Vehicle clustering for improving enhanced LTE-V2X network performance. In: 2017 European Conference on Networks and Communications (EuCNC), Oulu, pp. 1–5, June 2017

    Google Scholar 

  12. Wang, H., Li, X., Ji, H., Zhang, H.: Federated Offloading Scheme to Minimize Latency in MEC-Enabled Vehicular Networks 2018 IEEE Globecom Workshops (GC Wkshps), pp. 1–6. Abu Dhabi, United Arab Emirates (2018)

    Google Scholar 

  13. Guo, H., Liu, J., Zhang, J.: Efficient computation offloading for multi-access edge computing in 5G HetNets. In: 2018 IEEE International Conference on Communications (ICC), Kansas City pp. 1–6, May 2018

    Google Scholar 

  14. Guo, H., Liu, J.: Collaborative computation offloading for multiaccess edge computing over fiber-wireless networks. IEEE Trans. Veh. Technol. 67(5), 4514–4526 (2018)

    Article  Google Scholar 

  15. Desikan, K.E.S., Kotagi, V.J., Murthy, C.S.R.: Smart at right price: a cost efficient topology construction for fog computing enabled iot networks in smart cities. In: 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Bologna, pp. 1–7, September 2018

    Google Scholar 

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Acknowledgement

This work is supported by ROIS NII Open Collaborative Research 2021 (21FA03).

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Correspondence to Heli Zhang .

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zhang, H., Zhang, H., Shao, X., Ji, Y. (2022). Relay-Assisted Task Offloading Optimization for MEC-Enabled Internet of Vehicles. In: Calafate, C.T., Chen, X., Wu, Y. (eds) Mobile Networks and Management. MONAMI 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-030-94763-7_12

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  • DOI: https://doi.org/10.1007/978-3-030-94763-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-94762-0

  • Online ISBN: 978-3-030-94763-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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