面向海洋观监测传感网的计算卸载方法研究

苏新; 薛淏阳; 周一青; 朱金秀

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

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面向海洋观监测传感网的计算卸载方法研究

学术论文 | 更新时间：2024-06-06

- 面向海洋观监测传感网的计算卸载方法研究
- Research on computing offloading method for maritime observation monitoring sensor network
- 通信学报 2021年42卷第5期页码：149-163
- 作者机构：
  
  1. 河海大学物联网工程学院，江苏常州 231022
  2. 中国科学院计算技术研究所，北京100190
- 作者简介：
  
  [ "苏新（1986- ），男，河北霸州人，博士，河海大学教授、硕士生导师，主要研究方向为通信与计算融合、移动通信技术、边缘/雾计算、智慧海洋等" ]
  [ "薛淏阳（1996- ），男，山西临汾人，河海大学硕士生，主要研究方向为海洋网络、边缘/雾计算、计算卸载等" ]
  [ "周一青（1975- ），女，浙江杭州人，中国科学院计算技术研究所研究员、博士生导师，主要研究方向为通信与计算融合、移动边缘计算、存储通信、干扰管控等" ]
  [ "朱金秀（1972- ），女，江苏常州人，博士，河海大学副教授、硕士生导师，主要研究方向为神经网络、边缘/雾计算、数字通信等" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2021YFE0105500);国家自然科学基金资助项目(61801166)
- DOI：10.11959/j.issn.1000-436x.2021067
  中图分类号： TN929.52
- 网络首发：2021-05，
  
  纸质出版：2021-05-25
- 稿件说明：
移动端阅览
苏新, 薛淏阳, 周一青, 等. 面向海洋观监测传感网的计算卸载方法研究[J]. 通信学报, 2021,42(5):149-163.

Xin SU, Haoyang XUE, Yiqing ZHOU, et al. Research on computing offloading method for maritime observation monitoring sensor network[J]. Journal on Communications, 2021, 42(5): 149-163.
苏新, 薛淏阳, 周一青, 等. 面向海洋观监测传感网的计算卸载方法研究[J]. 通信学报, 2021,42(5):149-163. DOI： 10.11959/j.issn.1000-436x.2021067.

Xin SU, Haoyang XUE, Yiqing ZHOU, et al. Research on computing offloading method for maritime observation monitoring sensor network[J]. Journal on Communications, 2021, 42(5): 149-163. DOI： 10.11959/j.issn.1000-436x.2021067.

摘要

针对海洋网络节点间计算能力与通信资源的差异性，提出了一种基于海洋网络连通概率的边缘计算节点选取方法。根据海洋近岸与远岸的网络节点密度不同，分别建立2种卸载模型。在近岸场景下，提出多节点协同的卸载方法，利用基于海洋多节点协同卸载遗传算法求解；在远岸场景下，提出可容错的卸载方法，利用基于分组交叉学习粒子群算法求解。仿真结果表明，所提方法较传统方法可降低30%以上的网络延时并可节约20%以上的网络成本，极大提高了各类海事应用的用户体验。

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.

关键词

Keywords

references

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