TY - GEN
T1 - The Time-Extended V2V2I path Prediction Method for Multi-RSU VANET Data Offloading based on the Multi-Access Edge Computing (MEC) Architecture
AU - Huang, Chung Ming
AU - Wu, Tzu Yu
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported by the Ministry Of Science and Technology (MOST), Taiwan (R.O.C.) under the grant number MOST 108-2221-E-006-056-MY3.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In the Vehicle-to-Vehicle-to-Infrastructure (V2V2I) VANET data offloading scenario, the source vehicle Vs that wants to have VANET data offloading can use (i) a Vehicle to Infrastructure (V2I) link to do VANET data offloading when Vs is inside the signal coverage of a Road Side Unit (RSU), which is the traditional self-offloading scenario, i.e., Vs connects the RSU directly by itself, or (ii) a V2V2I path, which denotes a n-hop V2V2I path connecting Vs and the ahead/rear RSU, to do VANET data offloading when Vs is outside the signal coverage of the corresponding RSU. When the signal coverages of some ahead/rear RSUs are overlapped, the RSU handoff processing between the signal-overlapped RSUs need to be tackled such that the V2V2I data offloading time can be extended. This work uses the Multi-Access Edge Computing (MEC) architecture to find the n-hop V2V2I offloading path. Based on the periodically received context reports from vehicles and a time-extended prediction mechanism, the MEC server can find whether there are some candidate V2V2I offloading paths that exist in the coming time period or not. Then, the MEC server selects the best one as the V2V2I offloading path. The performance evaluation shown that the proposed method is better than the traditional self-offloading method and can enhance the data offloading performance.
AB - In the Vehicle-to-Vehicle-to-Infrastructure (V2V2I) VANET data offloading scenario, the source vehicle Vs that wants to have VANET data offloading can use (i) a Vehicle to Infrastructure (V2I) link to do VANET data offloading when Vs is inside the signal coverage of a Road Side Unit (RSU), which is the traditional self-offloading scenario, i.e., Vs connects the RSU directly by itself, or (ii) a V2V2I path, which denotes a n-hop V2V2I path connecting Vs and the ahead/rear RSU, to do VANET data offloading when Vs is outside the signal coverage of the corresponding RSU. When the signal coverages of some ahead/rear RSUs are overlapped, the RSU handoff processing between the signal-overlapped RSUs need to be tackled such that the V2V2I data offloading time can be extended. This work uses the Multi-Access Edge Computing (MEC) architecture to find the n-hop V2V2I offloading path. Based on the periodically received context reports from vehicles and a time-extended prediction mechanism, the MEC server can find whether there are some candidate V2V2I offloading paths that exist in the coming time period or not. Then, the MEC server selects the best one as the V2V2I offloading path. The performance evaluation shown that the proposed method is better than the traditional self-offloading method and can enhance the data offloading performance.
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U2 - 10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00110
DO - 10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00110
M3 - Conference contribution
AN - SCOPUS:85127598665
T3 - Proceedings - 2021 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing and International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2021
SP - 651
EP - 658
BT - Proceedings - 2021 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing and International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th IEEE International Conference on Dependable, Autonomic and Secure Computing, 19th IEEE International Conference on Pervasive Intelligence and Computing, 7th IEEE International Conference on Cloud and Big Data Computing and 2021 International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2021
Y2 - 25 October 2021 through 28 October 2021
ER -