Research Output

Vehicular Computation Offloading for Industrial Mobile Edge Computing

  Due to the limited local computation resource, industrial vehicular computation requires offloading the computation tasks with time-delay sensitive and complex demands to other intelligent devices (IDs) once the data is sensed and collected collaboratively. This paper considers offloading partial computation tasks of the industrial vehicles (IVs) to multiple available IDs of the industrial mobile edge computing (MEC), including unmanned aerial vehicles (UAVs), and the fixed-position MEC servers, to optimize the system cost including execution time, energy consumption, and the ID rental price. Moreover, to increase the access probability of IV by the UAVs, the geographical area is divided into small partitions and schedule the UAVs regarding the regional IV density dynamically. A minimum incremental task allocation (MITA) algorithm is proposed to divide the whole task and assign the divided units for the minimum cost increment each time. Experimental results show the proposed solution can significantly reduce the system cost.

  • Type:

    Article

  • Date:

    16 February 2021

  • Publication Status:

    In Press

  • DOI:

    10.1109/TII.2021.3059640

  • ISSN:

    1551-3203

  • Funders:

    New Funder

Citation

Zhao, L., Yang, K., Tan, Z., Song, H., Al-Dubai, A., & Zomaya, A. (in press). Vehicular Computation Offloading for Industrial Mobile Edge Computing. IEEE Transactions on Industrial Informatics, https://doi.org/10.1109/TII.2021.3059640

Authors

Keywords

Mobile edge computing; task allocation; unmanned aerial vehicles; game theory; industrial vehicular com- putation offloading

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