[1]薛 锋,张雅文,陈思光.基于 D2D 协同的边缘计算迁移机制研究[J].计算机技术与发展,2023,33(06):117-124.[doi:10. 3969 / j. issn. 1673-629X. 2023. 06. 018]
　XUE Feng,ZHANG Ya-wen,CHEN Si-guang.Research on Edge Computing Offloading Mechanism Based on D2D Collaboration[J].,2023,33(06):117-124.[doi:10. 3969 / j. issn. 1673-629X. 2023. 06. 018]
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基于 D2D 协同的边缘计算迁移机制研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
33
期数:
2023年06期
页码:
117-124
栏目:
移动与物联网络
出版日期:
2023-06-10

文章信息/Info

Title:
Research on Edge Computing Offloading Mechanism Based on D2D Collaboration
文章编号:
1673-629X(2023)06-0117-08
作者:
薛 锋; 张雅文; 陈思光
南京邮电大学 物联网学院,江苏 南京 210003
Author(s):
XUE Feng; ZHANG Ya-wen; CHEN Si-guang
School of Internet of Things,Nanjing University of Posts and Telecommunications,Nanjing 210003,China
关键词:
边缘计算; 计算迁移; 资源分配; D2D 通信; 用户协同; 动态权重
Keywords:
edge computing; computation offloading; resource allocation; D2D communication; user collaboration; dynamic weight
分类号:
TP393
DOI:
10. 3969 / j. issn. 1673-629X. 2023. 06. 018
摘要:
为了缓解边缘网络通信压力、降低物联网设备对服务节点的计算与通信负荷,提出了一种基于 Device-to-Device(D2D) 协同的边缘计算迁移机制。 具体而言,通过综合考虑 D2D 设备、边缘节点
的迁移决策以及传输功率分配,规划了一个任务完成总能耗最小化的优化问题,进一步,定义了 D2D 设备的积极性度量约束以促进 D2D 设备与普通用户间的协作。 同时,提出了基于动态感知蝙蝠群体的高效计算迁移算法( Dynamic Sensing Bat Population-Based Efficient ComputationOffloading Algorithm,DSBP-ECOA) 。 该算法融合经典蝙蝠算法思想,引入一种自适应的动态惯性权重,以通过实时感知环境变化调整蝙蝠群体的移动方向和速度,并采用混沌映射理论对种群进行初始化。 最后,仿真结果表明,所提方案能够以较快的速度收敛,并获得最优迁移和功率分配策略,与其他几种基准方案相比,该方案在降低系统能耗方面具有较大的优势。
Abstract:
In order to relieve the communication pressure of edge network and reduce the computing and communication load of Internetof Things ( IoT) devices to service nodes,we propose an edge computing offloading mechanism based on Device-to -Device ( D2D)collaboration. Specifically,based on the comprehensive consideration of offloading decisions and transmission power allocation,an optimization problem that minimizes the total energy consumption of task completion is formulated. Furthermore, the motivationmeasurement constraint of D2D device is defined to promote collaboration between cooperation users and common users. At the sametime,an efficient computation offloading algorithm based on dynamic sensing of bat population ( DSBP - ECOA) is proposed. Thealgorithm combines the ideas of classical bat algorithm,and introduces an adaptive dynamic inertia weight. Through sensing environmentin real time to adjust the movement direction and speed of bat population, and the chaotic mapping theory is used to initialize thepopulation. Finally, the simulation results show that the proposed scheme can converge at a faster speed, and achieve the optimaloffloading and power allocation strategy. Compared with other benchmark schemes,the proposed scheme has significant advantages in?
reducing system energy consumption.

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更新日期/Last Update: 2023-06-10