面向车联网边缘计算的智能计算迁移研究

doi:10.3969/j.issn.0255-8297.2020.05.009

Abstract

Abstract: To meet the requirements of offloading time optimization for computing tasks and load balance optimization for edge devices, an intelligent computing offloading method (ICOM) is proposed in this paper. Initially, a computing offloading model based on the real-world scenario is erected. Besides, the time model of task execution and the load balance model of edge devices are also established. Then, the non-dominant sorting genetic algorithm (NSGA-II) is used to realize the joint optimization of the offloading delay of computing tasks and the load balance of edge devices, so as to find effective computing offloading strategies for computing tasks. Finally, the multi-criteria decision making (MCDM) and the technique for order preference by similarity to an ideal solution (TOPSIS) are utilized to select the optimal computing offloading strategy. Experimental results show that ICOM enables computing tasks to be completed within the expected time, while also ensuring load balance of edge devices.

Key words: nternet of vehicles (IoV), edge computing, computing offloading, non-dominant sorting genetic algorithm (NSGA-II)

CLC Number:

TP338.6

MO Ruichao, XU Xiaolong, HE Qiang, LIU Qi, ZHAO Qingzhan. Intelligent Computing Offloading for Internet of Vehicles in Edge Computing[J]. Journal of Applied Sciences, 2020, 38(5): 779-791.

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Intelligent Computing Offloading for Internet of Vehicles in Edge Computing

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