负载约束的C-V2X车辆缓存节点选择算法

徐哲鑫; 高楷蒙; 贾文康; 吴怡

doi:10.11959/j.issn.1000-436x.2021065

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负载约束的C-V2X车辆缓存节点选择算法

学术论文 | 更新时间：2024-06-05

- 负载约束的C-V2X车辆缓存节点选择算法
- Vehicular cache nodes selection algorithm under load constraint in C-V2X
- 通信学报 2021年42卷第3期页码：171-182
- 作者机构：
  
  福建师范大学光电与信息工程学院，福建福州 350007
- 作者简介：
  
  [ "徐哲鑫（1985- ），男，福建福州人，博士，福建师范大学副教授，主要研究方向为无线自组织网、车联网。" ]
  [ "高楷蒙（1996- ），女，河南安阳人，福建师范大学硕士生，主要研究方向为无线自组织网、车联网等。" ]
  [ "贾文康（1969- ），男，台湾台北人，博士，福建师范大学教授，主要研究方向为网络协议、路由与转发。" ]
  [ "吴怡（1970- ），女，辽宁葫芦岛人，福建师范大学教授、博士生导师，主要研究方向为无线自组织网、无线视频传输。" ]
- 基金信息：
  
  国家自然科学基金资助项目(U1805262);国家自然科学基金资助项目(61871131);福建省自然科学基金资助项目(2020J01132418)
- DOI：10.11959/j.issn.1000-436x.2021065
  中图分类号： TN92
- 网络首发：2021-03，
  
  纸质出版：2021-03-25
- 稿件说明：
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徐哲鑫, 高楷蒙, 贾文康, 等. 负载约束的C-V2X车辆缓存节点选择算法[J]. 通信学报, 2021,42(3):171-182.

Zhexin XU, Kaimeng GAO, Wenkang JIA, et al. Vehicular cache nodes selection algorithm under load constraint in C-V2X[J]. Journal on Communications, 2021, 42(3): 171-182.
徐哲鑫, 高楷蒙, 贾文康, 等. 负载约束的C-V2X车辆缓存节点选择算法[J]. 通信学报, 2021,42(3):171-182. DOI： 10.11959/j.issn.1000-436x.2021065.

Zhexin XU, Kaimeng GAO, Wenkang JIA, et al. Vehicular cache nodes selection algorithm under load constraint in C-V2X[J]. Journal on Communications, 2021, 42(3): 171-182. DOI： 10.11959/j.issn.1000-436x.2021065.

摘要

为了解决城市环境下的 C-V2X 车辆拓扑高度动态化且车辆节点负载能力有限的问题，提高车辆缓存的利用率，减轻基站负荷，提出了负载约束下的车辆缓存节点选择算法。首先，通过定义链路稳定性度量，构建预测权重邻接矩阵，微观地描述车辆拓扑关系；其次，在负载约束和无重叠覆盖约束下构建目标函数，以最少的缓存节点实现全覆盖且最大化簇平均链路权重；最后，引入贪婪思想并合理定义节点状态，求解负载约束下车辆拓扑的最小支配集，并择优选择服务邻居节点。仿真结果表明，所提算法在缓存节点个数和簇平均链路权重均值方面接近全局最优，其重复应答率恒为零，请求应答率可达理论上界并可有效提高缓存源应答次数。

Abstract

In order to solve the problem that the C-V2X vehicle topology in urban environment was highly dynamic and the load capacity of vehicle nodes was limited

and improve the utilization of vehicular cache resources and reduce the load of base station

a vehicle cache nodes selection algorithm under load constraints was proposed.Firstly

by defining the link stability metric

the predicted weight adjacency matrix was constructed to describe the vehicular micro-topology in essence.Next

the objective function was further constructed under the load constraints and non-overlapping coverage constraint

which maximized the average link weight of the clusters by using the least cache nodes.Finally

the greedy concept was then introduced and the node states were reasonably defined.As a result

the minimum dominating set of the vehicle topology was figured out under the load constraints.Besides

the serviced neighbor nodes were then determined preferentially.The simulation results show that the proposed algorithm is close to the global optimal results in terms of the number of cache nodes and the average weight of cluster links.Moreover

the repeated response ratio of the proposed algorithm is always zero while the request response ratio can achieve the theoretical upper bound.Furthermore

the response times of cache resources can be also effectively improved.

关键词

Keywords

references

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