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计算机工程 ›› 2020, Vol. 46 ›› Issue (10): 33-40. doi: 10.19678/j.issn.1000-3428.0056981

• 热点与综述 • 上一篇    下一篇

移动边缘计算中基于用户体验的计算卸载方案

杨天1,2a, 田霖2a,2b, 孙茜2a,2b, 张宗帅2a,2b, 王园园2a,2b   

  1. 1. 重庆邮电大学 通信与信息工程学院, 重庆 400065;
    2. 中国科学院计算技术研究所 a. 无线通信技术研究中心;b. 移动计算与新型终端北京市重点实验室, 北京 100190
  • 收稿日期:2019-12-20 修回日期:2020-01-20 发布日期:2020-10-13
  • 作者简介:杨天(1994-),男,硕士研究生,主研方向为移动边缘计算;田霖,研究员;孙茜,博士;张宗帅、王园园,博士。
  • 基金资助:
    北京市自然科学基金(L172049)。

Computing Offloading Scheme Based on User Experiencein Mobile Edge Computing

YANG Tian1,2a, TIAN Lin2a,2b, SUN Qian2a,2b, ZHANG Zongshuai2a,2b, WANG Yuanyuan2a,2b   

  1. 1. College of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
    2a. Wireless Communication Technology Research Center;2b. Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2019-12-20 Revised:2020-01-20 Published:2020-10-13

摘要: 现有的移动边缘计算卸载方案多采用预先统一设置的方式确定权重因子,难以满足用户对时延和能耗的差异化需求。针对该问题,提出一种基于用户体验的计算卸载方案。将计算卸载问题定义为效用最大化问题,以任务执行时延和能耗增益率的加权和表示用户效用,同时考虑用户设备的续航能力,构造基于用户需求的自适应权重因子。在此基础上,将原优化问题拆分为资源分配和卸载决策两个子问题分别进行求解,得到最终的计算卸载策略。仿真结果表明,相比于固定权重因子的卸载方案,该方案能够满足用户的差异化需求,有效提升用户体验。

关键词: 移动边缘计算, 用户体验, 计算卸载, 资源分配, 混合整数非线性规划问题

Abstract: Most of the existing computing offloading schemes in Mobile Edge Computing(MEC) pre-set unified weight factors,which fail to meet the different requirements of users for delay and energy consumption.To address the problem,this paper proposes a computing offloading scheme based on user experience.The scheme defines the computing offloading problem as a utility maximization problem,and the user utility is represented by the weighted sum of task execution delay and the gain rate of energy consumption.Meanwhile,the scheme considers the battery life of the user’s device,and constructs the adaptive weight factor based on the user demand.On this basis,the original optimization problem is divided into two sub-problems of resource allocation and offloading decision,which are solved respectively to obtain the final computing offloading strategy.Simulation results show that compared with the offloading schemes with fixed weighting factors,this proposed scheme can meet different requirements of users and effectively improve the user experience.

Key words: Mobile Edge Computing(MEC), user experience, computing offloading, resource allocation, Mixed Integer Nonlinear Programming Problem(MINP)

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