In this paper, we investigate the latency minimization resource allocation for a multi-user augmented reality (AR) system based on mobile edge computing (MEC). First, we develop a novel data sharing model for the delay-sensitive AR tasks. Then, by integrating the partial offloading scheme into the task processing, we formulate a weighted-sum latency minimization problem to improve the quality of experience (QoE) for AR devices. Both the optimal task segmentation strategy and the optimal joint resource allocation are derived in closed-form. Finally, numerical results show that the proposed partial task offloading with data sharing scheme can achieve a better delay performance as compared against some benchmark schemes.


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    Titel :

    Data Offloading and Sharing for Latency Minimization in Augmented Reality Based on Mobile-Edge Computing


    Beteiligte:
    Liu, Wenliang (Autor:in) / Ren, Jinke (Autor:in) / Huang, Guan (Autor:in) / He, Yinghui (Autor:in) / Yu, Guanding (Autor:in)


    Erscheinungsdatum :

    01.08.2018


    Format / Umfang :

    159370 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch