Resource allocation optimization method for augment reality applications based on mobile edge computing

doi:10.11772/j.issn.1001-9081.2018071615

Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (1): 22-25.DOI: 10.11772/j.issn.1001-9081.2018071615

• 2018 CCF Annual Conference on Distributed and Parallel Computing Systems (DPCS 2018) • Previous Articles Next Articles

Resource allocation optimization method for augment reality applications based on mobile edge computing

YU Yun, LIAN Xiaocan, ZHU Yuhang, TAN Guoping

Communication and Information Systems Institute, Hohai University, Nanjing Jiangsu 211100, China

Received:2018-07-19 Revised:2018-08-16 Online:2019-01-10 Published:2019-01-21
Supported by:
This work is partially supported by the Fundamental Research Funds for the Central Universities (2015B18914), the Wireless Sensor Network and Communication Key Laboratory Open Project Fund of Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences (2016001).

增强现实场景下移动边缘计算资源分配优化方法

余韵, 连晓灿, 朱宇航, 谭国平

河海大学通信与信息系统研究所, 南京 211100

通讯作者: 谭国平
作者简介:余韵(1995-),女,浙江杭州人,硕士研究生,主要研究方向:移动边缘计算;连晓灿(1992-),女,福建泉州人,硕士研究生,主要研究方向:移动边缘计算、移动自组网;朱宇航(1998-),男,安徽安庆人,主要研究方向:移动边缘计算;谭国平(1975-),男,湖南澧县人,教授,博士,CCF会员,主要研究方向:移动自组网、无线多媒体通信、随机网络优化与控制、网络信息论。
基金资助:
中央高校基本科研业务费专项（2015B18914）；中国科学院上海微系统与信息技术研究所无线传感网与通信重点实验室开放课题项目（2016001）。

Abstract

Abstract:

Considering the time delay and the energy consumption of terminal equipment caused by high-speed data transmission and calculation, a transmission scheme with equal power allocation in uplink was proposed. Firstly, based on collaborative properties of Augment Reality (AR) services, a system model for AR characteristics was established. Secondly, system frame structure was analyzed in detail, and the constraints to minimize total energy consumption of system were established. Finally, with the time delay and energy consumption constraints satisfied, a mathematical model of Mobile Edge Computing (MEC) resource optimization based on convex optimization was established to obtain an optimal communication and computing resource allocation scheme. Compared with user independent transmission scheme, the total energy consumption of the proposed scheme with a maximum time delay of 0.1 s and 0.15 s was both 14.6%. The simulation results show that under the same conditions, compared with the optimization scheme based on user independent transmission, the equal power MEC optimization scheme considering cooperative transmission between users can significantly reduce the total energy consumption of system.

Key words: Augment Reality (AR), Mobile Edge Computing (MEC), resource allocation, collaborative computing migration, convex optimization

摘要：

针对高速数据传输及计算所带来时延和终端设备能耗问题，提出了一种在上行链路采用等功率分配的传输方案。首先，依据增强现实（AR）业务的协作属性建立了针对AR特性的系统模型；其次，详细分析了系统帧结构，建立以最小化系统消耗总能量为优化目标的约束条件；最后，在保障延迟和功耗满足约束的条件下，建立了基于凸优化的移动边缘计算（MEC）资源优化求解数学模型，从而获得最优的通信和计算资源分配方案。与独立传输相比，该方案在最大延迟时间分别为0.1 s和0.15 s时的总能耗降幅均为14.6%。仿真结果表明，在相同条件下，与基于用户独立传输的优化方案相比，考虑用户间协作传输的等功率MEC优化方案能显著减少系统消耗的总能量。

关键词: 增强现实, 移动边缘计算, 资源分配, 协作计算迁移, 凸优化

CLC Number:

YU Yun, LIAN Xiaocan, ZHU Yuhang, TAN Guoping. Resource allocation optimization method for augment reality applications based on mobile edge computing[J]. Journal of Computer Applications, 2019, 39(1): 22-25.

余韵, 连晓灿, 朱宇航, 谭国平. 增强现实场景下移动边缘计算资源分配优化方法[J]. 计算机应用, 2019, 39(1): 22-25.

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Resource allocation optimization method for augment reality applications based on mobile edge computing

增强现实场景下移动边缘计算资源分配优化方法

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