通信学报 ›› 2015, Vol. 36 ›› Issue (3): 21-32.doi: 10.11959/j.issn.1000-436x.2015055

• 学术论文 • 上一篇    下一篇

基于社会特征周期演化的机会移动网络路由转发策略

黄永锋1,董永强1,2(),张三峰1,2,吴国新1,2   

  1. 1 东南大学 计算机科学与工程学院,江苏 南京 211189
    2 东南大学 计算机网络和信息集成教育部重点实验室,江苏 南京 211189
  • 出版日期:2015-03-25 发布日期:2017-06-21
  • 基金资助:
    国家自然科学基金资助项目;国家高技术研究发展计划(“863”计划)基金资助项目;江苏省博士后科研基金资助项目;江苏省未来网络前瞻性研究基金资助项目

Message forwarding based on periodically evolving social characteristics in opportunistic mobile networks

Yong-feng HUANG1,Yong-qiang DONG1,2(),San-feng ZHANG1,2,Guo-xin WU1,2   

  1. 1 School of Computer Science and Engineering, Southeast University, Nanjing 211189, China
    2 Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing 211189, China
  • Online:2015-03-25 Published:2017-06-21
  • Supported by:
    The National Natural Science Foundation of China;The National High Technology Research and Development Program (863 Program) of China;Jiangsu Planned Project for Post-doctoral Research Funds;The Future Networks Prospective Research Program of Jiangsu Province

摘要:

针对分布式k团社区检测引起的超大社区问题,提出了具有节点退出机制的τ-window社区检测方法,相应提出了τ-window中心性估计。通过实验发现τ-window社区和τ-window中心性具有周期演化特性,利用该特性,提出TTL(time to live)社区检测和TTL中心性估计,以更准确预测消息生存期上节点的相遇。随后,利用TTL社区和TTL中心性作为转发测度,设计了新的机会移动网络路由算法PerEvo。实验结果表明,与现有的基于社会特征的路由算法比较,PerEvo在保持基本不变的传输开销的同时,有效提高了机会移动网络消息投递的成功率。

关键词: 机会移动网络, 社区, 中心性, 周期演化, 消息转发

Abstract:

To avoid monster community problem which suffered by distributed k-clique community detection, τ-window community detection was proposed. In addition, τ-window centrality estimation was put forward. By investigating the periodic evolution of τ-window community and τ-window centrality, two new metrics, TTL(time to live) community and TTL centrality, were proposed to improve the prediction of the node's encounter during the message's lifetime. Moreover, a social-aware routing algorithm, PerEvo, was then designed based on them. Extensive trace-driven simulation results show that PerEvo achieves higher message delivery ratio than the existing social-based forwarding schemes, while keep-ing similar routing overhead.

Key words: opportunistic mobile networks, community, centrality, periodic evolution, message forwarding

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