基于跨层链路质量感知的OLSR协议优化研究
DOI:
CSTR:
作者:
作者单位:

中国电子科技集团公司第五十四研究所

作者简介:

通讯作者:

中图分类号:

TP393

基金项目:

先进通信网全国重点实验室(FFX24641X005);国家重点研发计划资助(2022YFC3801100)


Research on Optimization of OLSR Protocol Based on Cross-Layer Link Quality Awareness
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对传统OLSR协议多点中继选择机制仅依赖拓扑覆盖而忽略链路动态质量的问题,提出了一种基于跨层设计的OLSR 改进方案,对MPR选择机制进行优化;构建跨层综合状态因子,融合物理层误比特率、MAC层帧接收成功率、MAC层队列长度等多维指标,设计拓展HELLO消息格式,新增CSE跨层字段,实现邻居节点状态的实时交互;设计新的MPR选择机制,将传统覆盖度优先策略优化为基于CSE加权的多目标决策模型,通过动态评分函数同时优化链路稳定性和负载均衡;仿真结果表明:CSE-OLSR在分组投递率、平均端到端时延等方面均优于传统OLSR,能够有效提高数据传输的稳定性和可靠性,适用高动态、高负载的MANETs场景。

    Abstract:

    Aiming at the issue that the traditional OLSR protocol's multipoint relay selection mechanism relies solely on topological coverage while ignoring the dynamic quality of links, an improved OLSR scheme based on cross-layer design is proposed to optimize the MPR selection mechanism. A cross-layer comprehensive state factor is constructed, integrating multi-dimensional metrics such as the physical layer's bit error rate, the MAC layer's frame reception success rate, and the MAC layer's queue length. The HELLO message format is extended to include a new CSE cross-layer field, enabling real-time interaction of neighbor node states. A new MPR selection mechanism is designed, optimizing the traditional coverage-first strategy into a multi-objective decision-making model weighted by CSE. This mechanism employs a dynamic scoring function to simultaneously enhance link stability and load balancing. Simulation results demonstrate that CSE-OLSR outperforms the traditional OLSR in terms of packet delivery rate and average end-to-end delay, effectively improving the stability and reliability of data transmission, making it suitable for highly dynamic and high-load MANETs scenarios.

    参考文献
    相似文献
    引证文献
引用本文
相关视频

分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2025-06-02
  • 最后修改日期:2025-06-29
  • 录用日期:2025-06-30
  • 在线发布日期:
  • 出版日期:
文章二维码