基于智能化用户协作的边缘计算任务卸载与资源分配优化

doi:10.11959/j.issn.2096-3750.2022.00303

Abstract

Abstract:

In order to deal with the increasingly scarce computing resources, a cooperative edge computing scheme was proposed, which makes full use of the idle resources among users to improve the overall data processing performance.To maximize the user utility, the target problem was formulated as an MINLP (mixed integer non-linear programming), and a learning-optimization-integrated method was proposed to jointly optimize the resource allocation and user offloading decisions.Simulation results show that the proposed scheme can produce a near-optimal solution in sub-second and effectively improve the system utility at least 85.4% compared to the considered benchmark methods.

Key words: mobile edge computing, utility maximization, convex optimization, reinforcement learning

CLC Number:

TN92

Xian LI, Suzhi BI, Hongru ZENG, Bin LIN, Xiaohui LIN. Collaborative task offloading and resource allocation optimization for intelligent edge devices[J]. Chinese Journal on Internet of Things, 2022, 6(4): 41-52.

Figures/Tables 7

References 11

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总任务数量/个	11	12	13	14	15
PSO算法计算时间/s	46.6	46.5	46.8	48.4	47.4
BCD算法计算时间/s	0.74	0.81	1.00	1.07	1.35
混合深度学习-优化算法计算时间/s	0.09	0.09	0.10	0.11	0.14

Collaborative task offloading and resource allocation optimization for intelligent edge devices

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