基于DQN的车载边缘网络任务分发卸载算法

doi:10.11959/j.issn.1000-436x.2020160

Abstract

Abstract:

In order to achieve the best balance between latency,computational rate and energy consumption,for a edge access network of IoV,a distribution offloading algorithm based on deep Q network (DQN) was considered.Firstly,these tasks of different vehicles were prioritized according to the analytic hierarchy process (AHP),so as to give different weights to the task processing rate to establish a relationship model.Secondly,by introducing edge computing based on DQN,the task offloading model was established by making weighted sum of task processing rate as optimization goal,which realized the long-term utility of strategies for offloading decisions.The performance evaluation results show that,compared with the Q-learning algorithm,the average task processing delay of the proposed method can effectively improve the task offload efficiency.

Key words: IoV, MEC, computational offloading, DQN, computational rate

CLC Number:

TP399

Haitao ZHAO,Tangwei ZHANG,Yue CHEN,Houlin ZHAO,Hongbo ZHU. Task distribution offloading algorithm of vehicle edge network based on DQN[J]. Journal on Communications, 2020, 41(10): 172-178.

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References 20

[1]	NING Z , FENG Y F , COLLOTTA M ,et al. Deep learning in edge of vehicles:exploring trirelationship for data transmission[J]. IEEE Transactions on Industrial Informatics, 2019,15(10): 5737-5746.
[2]	ZHOU H , XU W , CHEN J . Evolutionary V2X technologies toward the Internet of vehicles:challenges and opportunities[J]. Proceedings of the IEEE, 2020,108(2): 308-323.
[3]	POPLI S , JHA R K , JAIN S . A survey on energy efficient narrowband Internet of things (NBloT):architecture,application and challenges[J]. IEEE Access, 2019(7): 16739-16776.
[4]	谢人超, 廉晓飞, 贾庆民 ,等. 移动边缘计算卸载技术综述[J]. 通信学报, 2018,39(11): 138-155.
	XIE R C , LIAN X F , JIA Q M ,et al. Overview of mobile edge computing offload technology[J]. Journal on Communications, 2018,39(11): 138-155.
[5]	XIE J , JIA Y , CHEN Z ,et al. Efficient task completion for parallel offloading in vehicular fog computing[J]. China Communications, 2019,16(11): 42-45.
[6]	HUANG K B , ZHU G X , YOU C S ,et al. Communication,computing,and learning on the edge[C]// 2018 IEEE International Conference on Communication Systems. Piscataway:IEEE Press, 2018: 268-273.
[7]	MAO Y , YOU C , ZHANG J ,et al. A survey on mobile edge computing:the communication perspective[J]. IEEE Communications Surveys ＆ Tutorials, 2017,19(4): 2322-2358.
[8]	ZHANG J , LETAIEF K B . Mobile edge intelligence and computing for the Internet of vehicles[J]. Proceedings of the IEEE, 2020,108(2): 246-261.
[9]	KETYKO I , KECSKES L , NEMES C ,et al. Multi-user computation offloading as multiple knapsack problem for 5G mobile edge computing[C]// 2016 European Conference on Networks and Communications. Piscataway:IEEE Press, 2016: 225-229.
[10]	ZAHO J , LI Q , GONG Y ,et al. Computation offloading and resource allocation for cloud assisted mobile edge computing in vehicular networks[J]. IEEE Transactions on Vehicular Technology, 2019,68(8): 7944-7956.
[11]	MENG X , WANG W , WANG Y ,et al. Closed-form delay-optimal computation offloading[J]. Mobile Edge Computing Systems, 2019,18(10): 4653-4667.
[12]	DU J , ZHAO L , FENG J ,et al. Computation offloading and resource allocation in mixed fog/cloud computing systems with min-max fairness guarantee[J]. IEEE Transactions on Communications, 2017,66(4): 1-3.
[13]	郭辉, 芮兰兰, 高志鹏 . 车辆终端边缘网络中基于多参数 MDP 模型的动态服务迁移策略[J]. 通信学报, 2020,41(1): 1-14.
	GUO H , RUI L L , GAO Z P . Dynamic service migration strategy based on multi-parameter MDP model in vehicle edge network[J]. Journal on Communications, 2020,41(1): 1-14.
[14]	LI J , GAO H , LYU T ,et al. Deep reinforcement learning based computation offloading and resource allocation for MEC[C]// 2018 IEEE Wireless Communications and Networking Conference. Piscataway:IEEE Press, 2018: 1-6.
[15]	ARULKUMARAN K , DEISENROTH M P , BRUNDAGE M ,et al. Deep reinforcement learning:a brief survey[J]. IEEE Signal Processing Magazine, 2017,34(6): 26-38.
[16]	MAO Q , FEI H , QI H . Deep learning for intelligent wireless networks:a comprehensive survey[J]. IEEE Communications Surveys ＆ Tutorials, 2018,20(4): 2595-2621.
[17]	HUANG Y L , SUN W L . An AHP-based risk assessment for an industrial IoT cloud[C]// 2018 IEEE International Conference on Software Quality,Reliability and Security Companion. Piscataway:IEEE Press, 2018: 637-638.
[18]	余翔, 刘一勋, 石雪琴 ,等. 车联网场景下的移动边缘计算卸载策略[J]. 计算机工程, 2020,doi:10.19678/j.issn.1000-3428.0056850.
	YU X , LIU Y X , SHI X Q ,et al. Offloading strategy for mobile edge computing in Vehicle Network[J]. Computer Engineering, 2020,doi:10.19678/j.issn.1000-3428.0056850.
[19]	陈山枝, 胡金玲, 时岩 . LTE-V2X车联网技术、标准与应用[J]. 电信科学, 2018,34(4): 1-11.
	CHEN S Z , HU J L , SHI Y . LTE-V2X car networking technology,standards and applications[J]. Telecommunications Science, 2018,34(4): 1-11.
[20]	王寒松 . 车联网中基于 MEC 的计算任务卸载策略研究[D]. 北京:北京邮电大学, 2019.
	WANG H S . Research of computing offloading scheme for MEC-enabled vehicular networks[D]. Beijing:Beijing University of Posts and Telecommunications, 2019.

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