Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system is an appealing concept, where a fixed-wing UAV equipped with computing resources is used to help local resource-limited user devices (UDs) compute their tasks. In this paper, each UD has separable computing tasks to complete, which can be divided into two parts: one portion is processed locally and the other part is offloaded to the UAV. The UAV moves around above UDs and provides computing service in an orthogonal frequency division multiple access (OFDMA) manner. This paper aims to minimize the weighted sum energy consumption of the UAV and UDs by jointly optimizing resource allocation and UAV trajectory. The resulted optimization problem is nonconvex and challenging to solve directly. With that in mind, we develop an iterative algorithm for solving this problem based on the block coordinate descent method, which iteratively optimizes resource allocation variables and UAV trajectory variables till convergence. Simulation results show significant energy saving of our proposed solution compared to the benchmarks.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Joint Resource Allocation and Trajectory Design for UAV-assisted Mobile Edge Computing Systems


    Beteiligte:
    Ji, Jiequ (Autor:in) / Zhu, Kun (Autor:in) / Yi, Changyan (Autor:in) / Wang, Ran (Autor:in) / Niyato, Dusit (Autor:in)


    Erscheinungsdatum :

    01.12.2020


    Format / Umfang :

    239063 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    UAV-Assisted Edge computing with 3D Trajectory Design and Resource Allocation

    Wen, Pengle / Hu, Xiaoyan / Wong, Kai-Kit | IEEE | 2023



    Joint Offloading and Resource Allocation for Scalable Vehicular Edge Computing

    Wu, Wei / Wang, Qie / Wu, Xuanli et al. | IEEE | 2020


    Resource Awareness In Unmanned Aerial Vehicle-Assisted Mobile-Edge Computing Systems

    Chen, Xianfu / Chen, Tao / Zhao, Zhifeng et al. | IEEE | 2020


    Intelligent Resource Allocation in UAV-Enabled Mobile Edge Computing Networks

    Wang, Meng / Shi, Shuo / Gu, Shushi et al. | IEEE | 2020