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

Abstract

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

CLC Number:

TN92

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.

Figures/Tables 10

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

References 36

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