边云协同场景下基于强化学习的精英分层任务卸载策略研究

doi:10.11959/j.issn.2096-3750.2022.00258

Abstract

Abstract:

With the development of 5G and the enrichment of application functions, applications have put forward higher requirements on the computing capabilities of terminal devices.In order to improve the computing capabilities of terminal devices on applications and reduce the processing time of tasks, it is aimed at mobile edge computing environments, a task offloading method for edge-cloud collaboration was proposed，and an elite hierarchical evolutionary algorithm combined with reinforcement learning (RL-EHEA) was designed to perform offloading decisions, so that multiple tasks with dependencies and deadlines compete for computing resources.The simulation experiment results show that, compared with genetic algorithm (GA) and elite genetic algorithm (EGA), RL-EHEA can shorten task processing time and obtain better resource allocation strategy.

Key words: mobile edge computing, task offloading, edge-cloud collaboration, evolutionary algorithm, serial task

CLC Number:

TP391

Juan FANG, Zhiyuan YE, Mengyuan ZHANG, Jiamei SHI, Ziyi TENG. Research on elite hierarchical task offloading strategy based on reinforcement learning in edge-cloud collaboration scenario[J]. Chinese Journal on Internet of Things, 2022, 6(1): 91-100.

Figures/Tables 17

实验参数	取值
终端设备运行的应用程序数量N_p	[2,6]
应用程序包含的任务数量N_T	5
终端设备的CPU频率F_U/GHz	0.5
MEC 服务器的CPU频率F_M/GHz	5
云端的CPU频率F_C/GHz	15
任务计算所需的CPU周期D_i/GHz	[0.1,0.9]
任务大小d_i/MB	[0.5,1]
任务输出数据量O_i/MB	[0.01,0.03]
终端设备与MEC服务器的传输速率 $r_{i}^{U \to M} / (MB \cdot s^{- 1})$	[3.5,5]
MEC服务器间的传输速率 $r_{i}^{M \to N} / (MB \cdot s^{- 1})$	[10,20]
MEC服务器与云端的传输速率 $r_{i}^{M \to C} / (MB \cdot s^{- 1})$	[2,3]

References 16

[1]	ZHANG K , LENG S P , HE Y J ,et al. Mobile edge computing and networking for green and low-latency Internet of Things[J]. IEEE Communications Magazine, 2018,56(5): 39-45.
[2]	SABELLA D , VAILLANT A , KUURE P ,et al. Mobile-edge computing architecture:the role of MEC in the Internet of Things[J]. IEEE Consumer Electronics Magazine, 2016,5(4): 84-91.
[3]	NING Z L , XIA F , ULLAH N ,et al. Vehicular social networks:enabling smart mobility[J]. IEEE Communications Magazine, 2017,55(5): 16-55.
[4]	TALEB T , DUTTA S , KSENTINI A ,et al. Mobile edge computing potential in making cities smarter[J]. IEEE Communications Magazine, 2017,55(3): 38-43.
[5]	施巍松, 张星洲, 王一帆 ,等. 边缘计算:现状与展望[J]. 计算机研究与发展, 2019,56(1): 69-89.
	SHI W S , ZHANG X Z , WANG Y F ,et al. Edge computing:state-of-the-art and future directions[J]. Journal of Computer Research and Development, 2019,56(1): 69-89.
[6]	TANG L J , TANG B , KANG L Y ,et al. A novel task caching and migration strategy in multi-access edge computing based on the genetic algorithm[J]. Future Internet, 2019,11(8): 181.
[7]	LI Z , ZHU Q . Genetic algorithm-based optimization of offloading and resource allocation in mobile-edge computing[J]. Information, 2020,11(2): 83.
[8]	赵海涛, 张唐伟, 陈跃 ,等. 基于DQN的车载边缘网络任务分发卸载算法[J]. 通信学报, 2020,41(10): 172-178.
	ZHAO H T , ZHANG T W , CHEN Y ,et al. Task distribution offloading algorithm of vehicle edge network based on DQN[J]. Journal on Communications, 2020,41(10): 172-178.
[9]	WANG Y , TAO X F , ZHANG X F ,et al. Cooperative task offloading in three-tier mobile computing networks:an ADMM framework[J]. IEEE Transactions on Vehicular Technology, 2019,68(3): 2763-2776.
[10]	葛志诚, 徐恪, 陈靓 ,等. 一种移动内容分发网络的分层协同缓存机制[J]. 计算机学报, 2018,41(12): 2769-2786.
	GE Z C , XU K , CHEN L ,et al. A hierarchical cooperative caching strategy for mobile content delivery network[J]. Chinese Journal of Computers, 2018,41(12): 2769-2786.
[11]	XIAO Y , KRUNZ M . QoE and power efficiency tradeoff for fog computing networks with fog node cooperation[C]// Proceedings of IEEE INFOCOM 2017 - IEEE Conference on Computer Communications. Piscataway:IEEE Press, 2017: 1-9.
[12]	NGUYEN P D , HA V N , LE L B . Computation offloading and resource allocation for backhaul limited cooperative MEC systems[C]// Proceedings of 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall). Piscataway:IEEE Press, 2019: 1-6.
[13]	梁冰, 纪雯 . 基于次模优化的边云协同多用户计算任务迁移方法[J]. 通信学报, 2020,41(10): 25-36.
	LIANG B , JI W . Multiuser computation offloading for edge-cloud collaboration using submodular optimization[J]. Journal on Communications, 2020,41(10): 25-36.
[14]	NING Z L , DONG P R , KONG X J ,et al. A cooperative partial computation offloading scheme for mobile edge computing enabled Internet of Things[J]. IEEE Internet of Things Journal, 2019,6(3): 4804-4814.
[15]	REN J K , YU G D , HE Y H ,et al. Collaborative cloud and edge computing for latency minimization[J]. IEEE Transactions on Vehicular Technology, 2019,68(5): 5031-5044.
[16]	LI Y , ZHAO Y L , SHAO J . Empirical study on CNG refilling behaviors of different timescale based on boxplot method[J]. IOP Conference Series:Earth and Environmental Science, 2018,186: 012021.

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