Ready Player One: UAV-Clustering-Based Multi-Task Offloading for Vehicular VR/AR Gaming

  • Long Hu
  • , Yuanwen Tian
  • , Jun Yang*
  • , Tarik Taleb
  • , Lin Xiang
  • , Yixue Hao
  • *Tämän työn vastaava kirjoittaja

    Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

    86 Sitaatiot (Scopus)

    Abstrakti

    With rapid development of unmanned aerial vehicle (UAV) technology, application of UAVs for task offloading has received increasing interest in academia. However, real-time interaction between one UAV and the mobile edge computing node is required for processing the tasks of mobile end users, which significantly increases the system overhead and is unable to meet the demands of large-scale artificial intelligence (AI)-based applications. To tackle this problem, in this article, we propose a new architecture for UAV clustering to enable efficient multi-modal multi-task offloading. With the proposed architecture, the computing, caching, and communication resources are collaboratively optimized using Al-based decision making. This not only increases the efficiency of UAV clusters, but also provides insight into the fusion of computation and communication.

    AlkuperäiskieliEnglanti
    Artikkeli8726071
    Sivut42-48
    Sivumäärä7
    JulkaisuIEEE Network
    Vuosikerta33
    Numero3
    DOI - pysyväislinkit
    TilaJulkaistu - 1 toukok. 2019
    OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

    Rahoitus

    This work was supported by the National Key R&D Program of China (2018YFC1314605, 2017YFE0123600), the National Natural Science Foundation of China (Grant 61802138, Grant 618021:39) and the China Postdoctoral Science Foundation (No. 2018M632859). This work was partially supported by the Academy of Finland 6Genesis Flagship (Grant No. 318927) and the Primo-5G project, which has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 815191. The work of L. Xiang is supported by the European Research Council (ERC) project AGNOSTIC.

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