用于智能矿山移动边缘计算的二维动态匹配算法

赵端; 申澄洋; 史新国; 刘柯

doi:10.13272/j.issn.1671-251x.17782

用于智能矿山移动边缘计算的二维动态匹配算法

doi: 10.13272/j.issn.1671-251x.17782

赵端^{1, 2,},
申澄洋^{1, 2},
史新国³,
刘柯³

1.
中国矿业大学矿山互联网应用技术国家地方联合工程实验室, 江苏徐州　221116
2.
中国矿业大学信息与控制工程学院, 江苏徐州　221116
3.
淄博矿业集团有限责任公司信息中心, 山东淄博　255299

基金项目: 天地科技股份有限公司科技创新创业资金专项资助项目(2019-TD-ZD007)；淄博矿业集团有限责任公司“智慧矿山”关键技术研发开放基金项目（2019LH06）。

详细信息

作者简介:
赵端（1985—），男，河北承德人，副研究员，博士，主要研究方向为无线传感器网络、机器学习，E-mail:295318654@qq.com

中图分类号: TD67
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- 被引次数: 0
出版历程
- 收稿日期: 2021-05-10
- 修回日期: 2022-02-28
- 网络出版日期: 2022-04-25

Two-dimensional dynamic matching algorithm for mobile edge computing in intelligent mine

ZHAO Duan^{1, 2
,},
SHEN Chengyang^{1, 2},
SHI Xinguo³,
LIU Ke³

1.
The National Joint Engineering Laboratory of Internet Applied Technology of Mines, China University of Mining and Technology, Xuzhou 221116, China
2.
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China
3.
Information Center, Zibo Mining Group Co., Ltd., Zibo 255299, China

摘要

摘要: 针对智能矿山井下移动边缘计算（MEC）应用中存在的由于资源分配不合理，移动用户将任务卸载到非最优边缘服务器，导致额外的传输时间和执行延迟，从而造成总任务完成率下降的问题，提出了一种基于偏好的二维动态匹配算法，优化MEC系统中资源分配决策。将1个时隙内MEC系统中移动用户的位置、任务所需计算量等数据发送至边缘服务器，根据设定的偏好值大小，形成边缘服务器对移动用户的偏好表，同时移动用户根据物理距离的不同，对所有边缘服务器也形成偏好表，2张偏好表相结合形成一张二维动态偏好表，进而抽象为一个二维矩阵，通过基于偏好的二维动态匹配算法对二维矩阵进行处理，得到移动用户和边缘服务器的匹配优化结果。仿真结果表明：与常规MEC场景卸载算法相比，基于偏好的二维动态匹配算法能够有效缓解大量突发任务场景下总任务完成率下降的问题，在极端情况下总任务完成率能够达到60%以上。
- 智能矿山 /
- 移动边缘计算 /
- 边缘服务器 /
- 移动用户 /
- 二维动态匹配 /
- 偏好 /
- 总任务完成率
Abstract: In the application of mobile edge computing(MEC) in intelligent mine, the mobile users unload tasks to non-optimal edge servers due to unreasonable resource allocation, which leads to extra transmission time and execution delay, thus resulting in the decrease of the total task completion rate. In order to solve the above problem, a two-dimensional dynamic matching algorithm based on preference is proposed to optimize the resource allocation decision in MEC system. The data of the position of a mobile user in MEC system and the calculation amount required by a task in one time slot is sent to the edge server. The preference table of the edge server for the mobile user is formed according to the set preference value. At the same time, the preference table for all the edge servers is formed by the mobile user according to different physical distances. The two preference tables are combined to form a two-dimensional dynamic preference table, which is abstracted into a two-dimensional matrix. The two-dimensional matrix is processed by a two-dimensional dynamic matching algorithm based on preference, and the matching optimization results of mobile users and edge servers are obtained. The simulation results show that compared with the conventional MEC scene unloading algorithm, the preference-based two-dimensional dynamic matching algorithm can effectively alleviate the problem of the decrease of the total task completion rate in a large number of sudden task scenes, and can achieve the total task completion rate of more than 60% in extreme cases.
- intelligent mine /
- mobile edge computing /
- edge server /
- mobile user /
- two-dimensional dynamic matching /
- preference /
- total task completion rate

HTML全文

图 1 密集任务条件下MEC模型

Figure 1. Mobile edge computing model under intensive task conditions

下载: 全尺寸图片幻灯片

图 2 不同MEC资源分配算法总任务完成率对比

Figure 2. The results of comparison of different mobile edge computing resource allocation algorithms on task completion rate

下载: 全尺寸图片幻灯片

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