基于最优运输理论的物联网边缘计算资源优化机制

doi:10.11959/j.issn.2096-3750.2021.00225

Abstract

Abstract:

With the development of the Internet of things (IoT) and edge computing, the computation-intensive tasks of IoT devices can be offloaded to edge devices and processed at the edge of networks.Due to the variation of the distribution and computation requirements of IoT devices, the computation resources of edge networks need to be managed dynamically.The optimal transport theory was adopted to optimize the computation resources allocation in IoT networks.An optimized regional partition mechanism was proposed based on the distribution of IoT devices and locations of edge computing devices.Under constraints on the computing capabilities of edge computing devices, the energy consumption and delay of IoT devices were optimized.The simulation results show that, compared with the traditional Voronoi partition scheme, the proposed optimization mechanism shows better balance.The average transmitting power can be reduced by 21% and the average delay can be reduced by 45%.

Key words: Internet of things, edge computing, resource allocation, optimal transport theory, energy consumption, delay

CLC Number:

TN92

Qi ZHANG, Yuna JIANG, Xiaohu GE, Yonghui LI. Resource allocation based on optimal transport theory in IoT edge computing[J]. Chinese Journal on Internet of Things, 2021, 5(2): 60-70.

Figures/Tables 10

References 29

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参数	说明	数值
L _x、L_y	区域边长	1 000 m
M	边缘计算服务器数	4
(x_i,y_i)	边缘计算服务器坐标	（250,250）（750,250）（750,750）（250,750）
N	物联网设备数量	600
D	物联网设备需卸载数据量	100 MB
μ _x、μ_y	二维截断式高斯分布平均值	120 m、430 m

Resource allocation based on optimal transport theory in IoT edge computing

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