面向海洋观监测传感网的计算卸载方法研究

doi:10.11959/j.issn.1000-436x.2021067

Abstract

Abstract:

Considering the differences in computing capacity and communication resources of the maritime network nodes, a maritime network connectivity probability based method was proposed for selecting edge computing service nodes.Because of the different node densities in the near-shore and far-shore scenarios, two offloading models were established accordingly.In the near-shore scenario, a multi-node cooperative offloading method was proposed by using the genetic algorithm based on maritime multi-node cooperative offloading.In the far-shore scenario, a fault-tolerant offloading method was proposed based on the particle swarm algorithm with grouping cross learning.Simulation results show that compared with conventional methods, the proposed methods save over 30% network delay and reduces about 20% network costs, which can greatly enhance the maritime user experiences.

Key words: maritime network, multi-access edge computing, computing offloading, genetic algorithm, particle swarm optimization

CLC Number:

TN929.52

Xin SU, Haoyang XUE, Yiqing ZHOU, Jinxiu ZHU. Research on computing offloading method for maritime observation monitoring sensor network[J]. Journal on Communications, 2021, 42(5): 149-163.

Figures/Tables 18

参数描述	参数值
OUE计算能力 f_k /GHz	[1, 1.5]
中继节点计算能力 $f_{m_{k}} / GHz$	[2, 3.5]
海上基站计算能力 f_OBS /GHz	12
OUE计算功率 $P_{k}^{L} / W$	[0.8, 1]
OUE传输功率 $P_{k}^{tran} / W$	[0.3, 0.5]
OUE任务复杂度c_k /(cycle·bit^-1)	[800, 1 000]
船舶通信半径r /m	[100, 300]
基站通信半径R/m	1 200
船舶速度v /Knot	[20, 30]

References 24

[1]	ZHOU Y Q , LIU L , WANG L ,et al. Service-aware 6G:an intelligent and open network based on the convergence of communication,computing and caching[J]. Digital Communications and Networks, 2020,6(3): 253-260.
[2]	ZHOU Y Q , TIAN L , LIU L ,et al. Fog computing enabled future mobile communication networks:a convergence of communication and computing[J]. IEEE Communications Magazine, 2019,57(5): 20-27.
[3]	MACH P , BECVAR Z . Mobile edge computing:a survey on architecture and computation offloading[J]. IEEE Communications Surveys ＆Tutorials, 2017,19(3): 1628-1656.
[4]	XIAO Y , REN Z Y , ZHANG H L . A novel task allocation for maximizing reliability considering fault-tolerant in VANET real time systems[C]// 2017 IEEE 28th Annual International Symposium on Personal,Indoor,and Mobile Radio Communications. Piscataway:IEEE Press, 2017: 1-7.
[5]	SAFAVAT S , SAPAVATH N N , RAWAT D B . Recent advances in mobile edge computing and content caching[J]. Digital Communications and Networks, 2020,6(2): 189-194.
[6]	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. Survey on computation offloading in mobile edge computing[J]. Journal on Communications, 2018,39(11): 138-155.
[7]	QI Y L , TIAN L , ZHOU Y Q ,et al. Mobile edge computing-assisted admission control in vehicular networks:the convergence of communication and computation[J]. IEEE Vehicular Technology Magazine, 2019,14(1): 37-44.
[8]	ZHENG K , ZHENG Q , CHATZIMISIOS P ,et al. Heterogeneous vehicular networking:a survey on architecture,challenges,and solutions[J]. IEEE Communications Surveys ＆ Tutorials, 2015,17(4): 2377-2396.
[9]	LIU J , MAO Y Y , ZHANG J ,et al. Delay-optimal computation task scheduling for mobile-edge computing systems[C]// 2016 IEEE International Symposium on Information Theory. Piscataway:IEEE Press, 2016: 1451-1455.
[10]	KAMOUN M , LABIDI W , SARKISS M . Joint resource allocation and offloading strategies in cloud enabled cellular networks[C]// 2015 IEEE International Conference on Communications. Piscataway:IEEE Press, 2015: 5529-5534.
[11]	DENG M F , TIAN H , FAN B . Fine-granularity based application offloading policy in cloud-enhanced small cell networks[C]// 2016 IEEE International Conference on Communications Workshops. Piscataway:IEEE Press, 2016: 638-643.
[12]	WANG H S , LI X , JI H ,et al. Dynamic offloading scheduling scheme for MEC-enabled vehicular networks[C]// 2018 IEEE/CIC International Conference on Communications in China. Piscataway:IEEE Press, 2018: 206-210.
[13]	SHA K W , YANG T A , WEI W ,et al. A survey of edge computing-based designs for IoT security[J]. Digital Communications and Networks, 2020,6(2): 195-202.
[14]	WEI F , CHEN S X , ZOU W X . A greedy algorithm for task offloading in mobile edge computing system[J]. China Communications, 2018,15(11): 149-157.
[15]	YOU C S , HUANG K B , CHAE H ,et al. Energy-efficient resource allocation for mobile-edge computation offloading[J]. IEEE Transactions on Wireless Communications, 2017,16(3): 1397-1411.
[16]	GUO F X , ZHANG H L , JI H ,et al. An efficient computation offloading management scheme in the densely deployed small cell networks with mobile edge computing[J]. IEEE/ACM Transactions on Networking, 2018,26(6): 2651-2664.
[17]	刘锐 . 基于移动边缘计算的任务卸载策略研究[D]. 上海:东华大学, 2019.
	LIU R . Research on the task offloading strategy based on mobile edge computing[D]. Shanghai:Donghua University, 2019.
[18]	ZHAO H Y , WANG Y , SUN R J . Task proactive caching based computation offloading and resource allocation in mobile-edge computing systems[C]// 2018 14th International Wireless Communications ＆ Mobile Computing Conference. Piscataway:IEEE Press, 2018: 232-237.
[19]	SU X , MENG L L , HUANG J . Intelligent maritime networking with edge services and computing capability[J]. IEEE Transactions on Vehicular Technology, 2020,69(11): 13606-13620.
[20]	陈卓, 冯钢, 刘怡静 ,等. MEC中基于改进遗传模拟退火算法的虚拟网络功能部署策略[J]. 通信学报, 2020,41(4): 70-80.
	CHEN Z , FENG G , LIU Y J ,et al. Virtual network function deployment strategy based on improved genetic simulated annealing algorithm in MEC[J]. Journal on Communications, 2020,41(4): 70-80.
[21]	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.
[22]	WANG M Y , JIN H , ZHAO C L ,et al. Delay optimization of computation offloading in multi-hop ad hoc networks[C]// 2017 IEEE International Conference on Communications Workshops. Piscataway:IEEE Press, 2017: 314-319.
[23]	HUANG L , FENG X , ZHANG C ,et al. Deep reinforcement learning-based joint task offloading and bandwidth allocation for multi-user mobile edge computing[J]. Digital Communications and Networks, 2019,5(1): 10-17.
[24]	ZHANG H L , GUO J , YANG L C ,et al. Computation offloading considering fronthaul and backhaul in small-cell networks integrated with MEC[C]// 2017 IEEE Conference on Computer Communications Workshops. Piscataway:IEEE Press, 2017: 115-120.

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GCL-PSO算法	远海可容错优化问题
粒子位置	卸载策略
适应度值	系统总成本
种群	不同卸载策略集合

参数描述	参数值
任务数量N	8
传输带宽W /MHz	1
OUE计算能力 f_oue/GHz	1
移动边缘节点计算能力/GHz	[1, 3]
固定边缘节点计算能力/GHz	[6, 7]
OUE计算功率P_loc /W	1
OUE传输功率P_tran/W	0.4
任务复杂度c_n/(cycle·bit^-1)	800
信噪比SNR /dB	[30, 50]
船舶通信半径r /m	[100, 300]
基站通信半径R/m	1 000
船舶速度v /Knot	[15, 20]

Research on computing offloading method for maritime observation monitoring sensor network

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