基于最优运输理论的蜂窝网边缘卸载时延优化研究

doi:10.11959/j.issn.2096-3750.2023.00352

物联网学报 ›› 2023, Vol. 7 ›› Issue (4): 13-27.doi: 10.11959/j.issn.2096-3750.2023.00352

• 理论与技术 • 上一篇

基于最优运输理论的蜂窝网边缘卸载时延优化研究

吕翔宇, 肖泳, 钟祎, 李强, 葛晓虎

华中科技大学电子信息与通信学院，湖北武汉 430074

修回日期:2023-07-02 出版日期:2023-12-01 发布日期:2023-12-01
作者简介:吕翔宇（1996- ），男，华中科技大学电子信息与通信学院硕士生，主要研究方向为无线通信、边缘卸载、最优运输理论
肖泳（1980- ），男，博士，华中科技大学教授，主要研究方向为网络人工智能、边缘计算、通信网络博弈理论等
钟祎（1989- ），男，博士，华中科技大学副教授，主要研究方向为无线干扰管理、资源分配等
李强（1984- ），男，博士，华中科技大学教授，主要研究方向为无线协作通信、认知无线电/协作频谱共享、无线信息能量同传、物联网、边缘计算、边缘缓存等
葛晓虎（1972- ），男，博士，华中科技大学教授，主要研究方向为移动通信、无线网络中的流量建模、绿色通信等
基金资助:
国家自然科学基金资助项目(U2001210);国家自然科学基金资助项目(62071190);国家重点研发计划(2020YFB1807700);湖北省重点研发计划(2021BAA015)

Research on edge offloading delay optimization of cellular networks based on optimal transport theory

Xiangyu LYU, Yong XIAO, Yi ZHONG, Qiang LI, Xiaohu GE

School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China

Revised:2023-07-02 Online:2023-12-01 Published:2023-12-01
Supported by:
The National Natural Science Foundation of China(U2001210);The National Natural Science Foundation of China(62071190);The Key Research and Development Program of China(2020YFB1807700);The Key Research and Development Program of Hubei Province(2021BAA015)

摘要/Abstract

摘要：

随着物联网的发展，蜂窝网络中接入了大量的用户设备。由于用户设备空间分布和应用需求的变化，需要对用户设备卸载决策进行动态调整。综合考虑网络中用户设备空间分布、应用需求、基站侧边缘服务器的处理能力等参数信息，从分布角度出发，优化用户设备的卸载决策。基于最优运输理论，提出一种时延优化算法。通过合理规划网络中用户设备的卸载基站，降低用户设备计算任务卸载过程的平均时延。仿真结果表明，所提基于时延优化的卸载机制能使平均时延降低81.06%，并能均衡各基站之间处理的业务量。

关键词: 边缘卸载, 最优运输理论, 时延优化, 物联网

Abstract:

With the development of the internet of things, a large number of user device (UD) were connected to cellular network.Since the changes in the spatial distribution of UD and application requirements, it is necessary to dynamically adjust the UD’ offloading decision.Comprehensively considering various parameter information in the networks such as the spatial distribution of UD, application requirements, and the processing capability of the edge servers on the base station (BS) side, the offloading decision of UD were optimized from the perspective of distribution.Based on the optimal transport theory, a delay optimization algorithm was proposed to reduce the average delay of the UD’ computing tasks offloading process by reasonably planning the offloading BS of the UD in the networks.The simulation results show that the average delay can be reduced by 81.06% using the proposed offloading mechanism based on delay optimization, and the traffic handled by each BS is balanced.

Key words: edge offloading, optimal transport theory, delay optimization, IoT

中图分类号:

TN92

吕翔宇, 肖泳, 钟祎, 李强, 葛晓虎. 基于最优运输理论的蜂窝网边缘卸载时延优化研究[J]. 物联网学报, 2023, 7(4): 13-27.

Xiangyu LYU, Yong XIAO, Yi ZHONG, Qiang LI, Xiaohu GE. Research on edge offloading delay optimization of cellular networks based on optimal transport theory[J]. Chinese Journal on Internet of Things, 2023, 7(4): 13-27.

图/表 10

图1

表1

仿真参数"

参数	说明	数值
$L_{x} 、 L_{y}$	矩形区域边长	1 000 m
$μ_{x} 、 μ_{y}$	二维截断高斯分布的均值	330 m、350 m
$σ_{x} 、 σ_{y}$	二维截断高斯分布的标准差	300、300
γ	数据包中数据量的均值	10 kbit
${(X_{i}, Y_{i})}_{i \in M}$	基站位置坐标	(200,200)(200,800)
		(400,400)(800,200)
		(800,800)
f	基站侧MEC服务器的频率	30 GHz
ω	处理单比特数据所需CPU周期数	400 cycle/bit
U	用户设备数量	8 000
N₀	噪声功率密度	10^-11W
ϑ	瑞利分布标准差	0.5
N	天线根数	4
δ	回传结果数据量与上传任务数据量之间的比例	0.2
$λ_{\max}$	用户设备单位时间内产生数据包个数的最大值	4
α	路径损耗指数	4
${P_{d}^{i}}_{i \in M}$	基站发射功率	1W
P _u	用户设备发射功率	0.3 W
B	上、下行信道传输带宽	10 MHz

表1

图2

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基于最优运输理论的蜂窝网边缘卸载时延优化研究

Research on edge offloading delay optimization of cellular networks based on optimal transport theory

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