移动边缘计算中基于资源联合分配的部分计算卸载方法

doi:10.11959/j.issn.2096-3750.2023.00313

物联网学报 ›› 2023, Vol. 7 ›› Issue (1): 140-148.doi: 10.11959/j.issn.2096-3750.2023.00313

移动边缘计算中基于资源联合分配的部分计算卸载方法

刘耀¹^,², 何岳园³, 周红静³, 李超良³, 李闯²^,³

¹ 湖南工商大学数字传媒与人文学院，湖南长沙 410205
² 长沙人工智能社会实验室，湖南长沙 410205
³ 湖南工商大学计算机学院，湖南长沙 410205

修回日期:2022-11-21 出版日期:2023-03-30 发布日期:2023-03-01
作者简介:刘耀（1976- ），男，博士，湖南工商大学副教授，主要研究方向为边缘计算、移动社会网络等
何岳园（1994- ），男，湖南工商大学硕士生，主要研究方向为移动边缘计算等
周红静（1976- ），女，湖南工商大学讲师，主要研究方向为移动边缘计算、机会网络、移动社会网络等
李超良（1972- ），男，博士，湖南工商大学讲师，主要研究方向为物联网、隐私保护、区块链等
李闯（1990- ），男，博士，湖南工商大学讲师，主要研究方向为物联网、高性能计算、并行计算等
基金资助:
国家自然科学基金资助项目(62002115);湖南省教育厅科学研究项目(20C0538);湖南省教育厅科学研究项目(21A0376);湖南省自然科学基金资助项目(2020JJ4250);湖南省社会科学成果评审委员会课题(XSP21YBZ113);青年教师创新驱动计划项目(2020QD08)

Partial computation offloading method based on joint resource allocation for mobile edge computing

Yao LIU¹^,², Yueyuan HE³, Hongjing ZHOU³, Chaoliang LI³, Chuang LI²^,³

¹ School of Digital Media and Humanities, Hunan University of Technology and Business, Changsha 410205, China
² Changsha Social Laboratory of Artificial Intelligence, Changsha 410205, China
³ School of Computer Science, Hunan University of Technology and Business, Changsha 410205, China

Revised:2022-11-21 Online:2023-03-30 Published:2023-03-01
Supported by:
The National Natural Science Foundation of China(62002115);The Scientific Research Project of the Department of Education of Hunan Province(20C0538);The Scientific Research Project of the Department of Education of Hunan Province(21A0376);The Natural Science Foundation of Hunan Province(2020JJ4250);The Project of Hunan Social Science Achievement Appraisal Committee(XSP21YBZ113);The Project of Innovation Driven Program for Young Teachers(2020QD08)

摘要/Abstract

摘要：

为了满足用户计算密集型任务的需求，解决移动终端计算资源和能量有限的问题，针对正交频分多址的多用户移动边缘计算系统，以任务时延为主要优化目标，设置任务时限、设备能量、通信资源等约束条件，提出了一个结合通信和边缘服务器计算资源分配的部分卸载方法。该方法在满足用户最低时延的条件下设置初始卸载比和分配通信资源，然后根据服务器计算能力来分配剩余计算资源，最后根据资源分配情况优化卸载比。仿真结果表明，该方法能够减少任务计算的时延和移动终端的能量消耗。

关键词: 移动边缘计算, 计算卸载, 资源分配

Abstract:

In order to meet the requirements of users for computing-intensive tasks and solve the problems of limited computing resources and energy of mobile terminals, a partial offloading method was proposed for multi-user mobile edge computing system with orthogonal frequency division multiple access by setting constraints such as task delay, device energy and communication resources, aiming at optimizing task delay.The initial offloading ratio was set and the communication resource was allocated under the condition of satisfying the user’s minimum delay.And then the remaining computing resource was allocated according to the server’s computing capability.Finally, the offload ratio was optimized according to the resource allocation.Simulation results show that this method can reduce the delay of task computing and the energy consumption of mobile terminals.

Key words: mobile edge computing, computation offloading, resource allocation

中图分类号:

TP393

刘耀, 何岳园, 周红静, 李超良, 李闯. 移动边缘计算中基于资源联合分配的部分计算卸载方法[J]. 物联网学报, 2023, 7(1): 140-148.

Yao LIU, Yueyuan HE, Hongjing ZHOU, Chaoliang LI, Chuang LI. Partial computation offloading method based on joint resource allocation for mobile edge computing[J]. Chinese Journal on Internet of Things, 2023, 7(1): 140-148.

图/表 5

表1

图1

图2

图3

图4

参考文献 30

[1]	CISCO. CISCO annual internet report (2018–2023)[EB]. 2020.
[2]	MACH P , BECVAR Z . Mobile edge computing:a survey on architecture and computation offloading[J]. IEEE Communications Surveys ＆Tutorials, 2017,19(3): 1628-1656.
[3]	张厚浩, 李晗琳, 高林 . 移动边缘计算中的分层资源部署与共享策略[J]. 物联网学报, 2021,5(1): 11-18.
	ZHANG H H , LI H L , GAO L . Hierarchical resource deployment and sharing strategy in mobile edge computing[J]. Chinese Journal on Internet of Things, 2021,5(1): 11-18.
[4]	ABBAS N , ZHANG Y , TAHERKORDI A ,et al. Mobile edge computing:a survey[J]. IEEE Internet of Things Journal, 2018,5(1): 450-465.
[5]	NGUYEN Q H , DRESSLER F . A smartphone perspective on computation offloading—A survey[J]. Computer Communications, 2020(159): 133-154.
[6]	LIN L , LIAO X F , JIN H ,et al. Computation offloading toward edge computing[J]. Proceedings of the IEEE, 2019,107(8): 1584-1607.
[7]	JIANG C , CHENG X , GAO H ,et al. Toward computation offloading in edge computing:a survey[J]. IEEE Access, 2019(7): 131543-131558.
[8]	ZHANG T Y , CHIANG Y H , BORCEA C ,et al. Learning-based offloading of tasks with diverse delay sensitivities for mobile edge computing[C]// Proceedings of 2019 IEEE Global Communications Conference. Piscataway:IEEE Press, 2019: 1-6.
[9]	XIAO K L , GAO Z P , YAO C C ,et al. Task offloading and resources allocation based on fairness in edge computing[C]// Proceedings of 2019 IEEE Wireless Communications and Networking Conference. Piscataway:IEEE Press, 2019: 1-6.
[10]	亓晋, 孙海蓉, 巩锟 ,等. 移动边缘计算中基于信誉值的智能计算卸载模型研究[J]. 通信学报, 2020,41(7): 141-151.
	QI J , SUN H R , GONG K ,et al. Research on intelligent computing offloading model based on reputation value in mobile edge computing[J]. Journal on Communications, 2020,41(7): 141-151.
[11]	夏士超, 姚枝秀, 鲜永菊 ,等. 移动边缘计算中分布式异构任务卸载算法[J]. 电子与信息学报, 2020,42(12): 2891-2898.
	XIA S C , YAO Z X , XIAN Y J ,et al. A distributed heterogeneous task offloading methodology for mobile edge computing[J]. Journal of Electronics ＆ Information Technology, 2020,42(12): 2891-2898.
[12]	MUKHERJEE M , KUMAR S , SHOJAFAR M ,et al. Joint task offloading and resource allocation for delay-sensitive fog networks[C]// Proceedings of ICC 2019 - 2019 IEEE International Conference on Communications. Piscataway:IEEE Press, 2019: 1-7.
[13]	YUE S , REN J,QIAON ,et al. TODG:distributed task offloading with delay guarantees for edge computing[J]. IEEE Transactions on Parallel and Distributed Systems, 2022,33(7): 1650-1665.
[14]	代美玲, 刘周斌, 郭少勇 ,等. 基于终端能耗和系统时延最小化的边缘计算卸载及资源分配机制[J]. 电子与信息学报, 2019,41(11): 2684-2690.
	DAI M L , LIU Z B , GUO S Y ,et al. A computation offloading and resource allocation mechanism based on minimizing devices energy consumption and system delay[J]. Journal of Electronics ＆ Information Technology, 2019,41(11): 2684-2690.
[15]	喻鹏, 张俊也, 李文璟 ,等. 移动边缘网络中基于双深度 Q 学习的高能效资源分配方法[J]. 通信学报, 2020,41(12): 148-161.
	YU P , ZHANG J Y , LI W J ,et al. Energy-efficient resource allocation method in mobile edge network based on double deep Q-learning[J]. Journal on Communications, 2020,41(12): 148-161.
[16]	JO?ILO S , DáN G . Wireless and computing resource allocation for selfish computation offloading in edge computing[C]// Proceedings of IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. Piscataway:IEEE Press, 2019: 2467-2475.
[17]	ESHRAGHI N , LIANG B . Joint offloading decision and resource allocation with uncertain task computing requirement[C]// Proceedings of IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. Piscataway:IEEE Press, 2019: 1414-1422.
[18]	ZHU X , CHEN S G , CHEN S L ,et al. Energy and delay co-aware computation offloading with deep learning in fog computing networks[C]// Proceedings of 2019 IEEE 38th International Performance Computing and Communications Conference. Piscataway:IEEE Press, 2019: 1-6.
[19]	GAO Y , ZHANG H R , YU F ,et al. Joint computation offloading and resource allocation for mobile-edge computing assisted ultra-dense networks[J]. Journal of Communications and Information Networks, 2022,7(1): 96-106.
[20]	VU T T , HOANG D T , PHAN K T ,et al. Energy-based proportional fairness for task offloading and resource allocation in edge computing[C]// Proceedings of ICC 2022 - IEEE International Conference on Communications. Piscataway:IEEE Press, 2022: 1912-1917.
[21]	TANG H J , WU H M , ZHAO Y B ,et al. Joint computation offloading and resource allocation under task-overflowed situations in mobile-edge computing[J]. IEEE Transactions on Network and Service Management, 2022,19(2): 1539-1553.
[22]	WANG C , LIANG C , YU F R ,et al. Computation offloading and resource allocation in wireless cellular networks with mobile edge computing[J]. IEEE Transactions on Wireless Communications, 2017,16(8): 4924-4938.
[23]	LI Q , ZHAO J , GONG Y . Cooperative computation offloading and resource allocation for mobile edge computing[C]// Proceedings of 2019 IEEE International Conference on Communications Workshops. Piscataway:IEEE Press, 2019: 1-6.
[24]	BOZORGCHENANI A , TARCHI D , CORAZZA G E . Mobile edge computing partial offloading techniques for mobile urban scenarios[C]// Proceedings of 2018 IEEE Global Communications Conference. Piscataway:IEEE Press, 2018: 1-6.
[25]	BI S Z , ZHANG Y J . Computation rate maximization for wireless powered mobile-edge computing with binary computation offloading[J]. IEEE Transactions on Wireless Communications, 2018,17(6): 4177-4190.
[26]	MAHMOOD A , AHMED A , NAEEM M ,et al. Partial offloading in energy harvested mobile edge computing:a direct search approach[J]. IEEE Access, 2020(8): 36757-36763.
[27]	WANG Z L , DU H W , YE Q . HTR:a joint approach for task offloading and resource allocation in mobile edge computing[C]// Proceedings of ICC 2021 - IEEE International Conference on Communications. Piscataway:IEEE Press, 2021: 1-6.
[28]	崔玉亚, 张德干, 张婷 ,等. 一种面向移动边缘计算的多用户细粒度任务卸载调度方法[J]. 电子学报, 2021,49(11): 2202-2207.
	CUI Y Y , ZHANG D G , ZHANG T ,et al. A multi-user fine-grained task offloading scheduling approach of mobile edge computing[J]. Acta Electronica Sinica, 2021,49(11): 2202-2207.
[29]	SALEEM U , LIU Y , JANGSHER S ,et al. Performance guaranteed partial offloading for mobile edge computing[C]// Proceedings of 2018 IEEE Global Communications Conference. Piscataway:IEEE Press, 2018: 1-6.
[30]	WANG L Y , ZHANG G L . Deep reinforcement learning based joint partial computation offloading and resource allocation in mobility-aware MEC system[J]. China Communications, 2022,19(8): 85-99.

参数	数值
服务器的计算能力/GHz	10
网络总带宽/MHz	20
正交子信道数量	64
每个用户的任务量/KB	[200, 1 000]
任务计算时延限制/ms	[50, 100]
用户终端计算能力/GHz	[0.1, 1]
计算单位比特所需的CPU周期数	[500, 1 500]
每个CPU周期的能耗范围/J	[0.5, 2]×10^-10J
最大发射功率/dBm	23
信道噪声功率/dB	-100

移动边缘计算中基于资源联合分配的部分计算卸载方法

Partial computation offloading method based on joint resource allocation for mobile edge computing

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献 30

相关文章 15

Metrics

推荐阅读 0

[1]	王志宏, 冷甦鹏, 熊凯. 面向无人机集群协同感知的多智能体资源分配策略[J]. 物联网学报, 2023, 7(1): 18-26.
[2]	汤蓓, 王倩, 陈思光. 融合射频能量采集的协同节能计算迁移研究[J]. 物联网学报, 2023, 7(1): 83-92.
[3]	苏麟, 党小超, 郝占军, 汝春瑞, 尚旭. 基于WPT-MEC的动态自适应卸载方法[J]. 物联网学报, 2022, 6(4): 128-138.
[4]	李贤, 毕宿志, 曾泓儒, 林彬, 林晓辉. 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[J]. 物联网学报, 2022, 6(4): 41-52.
[5]	孙君, 赵尚维康. 工业物联网中基于Sarsa算法的节能计算卸载方案[J]. 物联网学报, 2022, 6(3): 82-90.
[6]	陈九九, 郭彩丽, 冯春燕, 刘传宏. 智能网联环境下面向语义通信的资源分配[J]. 物联网学报, 2022, 6(3): 47-57.
[7]	方娟, 叶志远, 张梦媛, 史佳眉, 滕自怡. 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[J]. 物联网学报, 2022, 6(1): 91-100.
[8]	苏新, 江苏, 周一青. 面向海洋观监测传感网的移动终端位置隐私保护研究[J]. 物联网学报, 2021, 5(4): 26-36.
[9]	徐勇军, 杨浩克, 叶迎晖, 陈前斌, 卢光跃. 反向散射通信网络资源分配综述[J]. 物联网学报, 2021, 5(3): 56-69.
[10]	张琪, 蒋宇娜, 葛晓虎, 李永会. 基于最优运输理论的物联网边缘计算资源优化机制[J]. 物联网学报, 2021, 5(2): 60-70.
[11]	路静, 李晗琳, 高林. 移动边缘计算任务切分与最优卸载算法设计[J]. 物联网学报, 2021, 5(2): 78-86.
[12]	张厚浩, 李晗琳, 高林. 移动边缘计算中的分层资源部署与共享策略[J]. 物联网学报, 2021, 5(1): 11-18.
[13]	嵇介曲, 朱琨, 易畅言, 王然. 多无人机辅助移动边缘计算中的任务卸载和轨迹优化[J]. 物联网学报, 2021, 5(1): 27-35.
[14]	周鹏,徐金城,杨博. 工业物联网中基于边缘计算的跨域计算资源分配与任务卸载[J]. 物联网学报, 2020, 4(2): 96-104.
[15]	代玥玥,张科,张彦. 区块链赋能6G[J]. 物联网学报, 2020, 4(1): 111-120.