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

应用科学学报 ›› 2020, Vol. 38 ›› Issue (5): 779-791.doi: 10.3969/j.issn.0255-8297.2020.05.009

• 智能计算新技术 • 上一篇

面向车联网边缘计算的智能计算迁移研究

莫瑞超¹, 许小龙¹, 何强², 刘琦¹, 赵庆展³

1. 南京信息工程大学计算机与软件学院, 南京 210044;
2. 斯威本科技大学软件和电子工程学院, 墨尔本 VIC 3122;
3. 石河子大学信息科学与技术学院, 新疆石河子 832003

收稿日期:2020-06-15 发布日期:2020-10-14
通信作者: 许小龙,博士,讲师,研究方向为边缘计算、服务计算.E-mail:njuxlxu@gmail.com E-mail:njuxlxu@gmail.com
基金资助:
国家自然科学基金（No.61702277）；兵团财政科技计划项目（No.2020DB005，No.2017DB005）资助

Intelligent Computing Offloading for Internet of Vehicles in Edge Computing

MO Ruichao¹, XU Xiaolong¹, HE Qiang², LIU Qi¹, ZHAO Qingzhan³

1. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China;
2. School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne VIC 3122, Australia;
3. College of Information Science and Technology, Shihezi University, Shihezi 832003, Xinjiang, China

Received:2020-06-15 Published:2020-10-14

摘要/Abstract

摘要： 为了满足车联网中车载任务所面临的服务迁移时间优化与边缘设备的资源负载优化需求，提出了一种面向车联网边缘计算的智能计算迁移方法（intelligent computingoffloading method，ICOM）.首先构建了车联网边缘计算系统资源模型、执行时间模型、边缘设备负载均衡模型；然后利用非支配排序遗传算法（non-dominant sorting genetic algorithm，NSGA-II）实现了对车载计算任务的迁移时间和边缘设备的负载均衡进行联合优化，从而为车载计算任务找到有效的计算迁移策略；最后根据多目标决策准则（multi-criteria decisionmaking，MCDM）和逼近理想解排序法（technique for order preference by similarity to anideal solution，TOPSIS）选择出最优的计算迁移策略.实验结果表明，ICOM方法能够使车载计算任务在期望时间内完成，同时也保证边缘设备的负载均衡.

关键词: 车联网, 边缘计算, 计算迁移, 非支配排序遗传算法

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)

中图分类号:

TP338.6

莫瑞超, 许小龙, 何强, 刘琦, 赵庆展. 面向车联网边缘计算的智能计算迁移研究[J]. 应用科学学报, 2020, 38(5): 779-791.

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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面向车联网边缘计算的智能计算迁移研究

Intelligent Computing Offloading for Internet of Vehicles in Edge Computing

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