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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    Title :

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


    Contributors:
    Liu, Wenliang (author) / Ren, Jinke (author) / Huang, Guan (author) / He, Yinghui (author) / Yu, Guanding (author)


    Publication date :

    2018-08-01


    Size :

    159370 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English