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; 董永强; 张三峰; 吴国新

doi:10.11959/j.issn.1000-436x.2015055

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基于社会特征周期演化的机会移动网络路由转发策略

学术论文 | 更新时间：2024-06-05

- 基于社会特征周期演化的机会移动网络路由转发策略
- Message forwarding based on periodically evolving social characteristics in opportunistic mobile networks
- 通信学报 2015年36卷第3期页码：21-32
- 作者机构：
  
  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
- 作者简介：
  
  [ "黄永锋（1978-），男，江苏溧阳人，东南大学博士生，主要研究方向为云计算环境下的内容分发、时间演化的动态连通网络等。" ]
  [ "董永强（1973-），男，河南渑池人，博士，东南大学副研究员，主要研究方向为网络体系结构、移动网络计算。" ]
  [ "张三峰（1979-），男，山东金乡人，博士，东南大学讲师，主要研究方向为P2P网络、信任管理、移动自组网等。" ]
  [ "吴国新（1956-），男，安徽芜湖人，东南大学教授、博士生导师，主要研究方向为网络协议、网络安全、自组网等。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61272532;61370209;61300200;61472080);国家高技术研究发展计划(863“”计划)基金资助项目;The National High Technology Research and Development of China (863 Program)(2013AA013503);江苏省博士后科研基金资助项目;Jiangsu Planned Project for Post-doctoral Research Funds(1402039B);江苏省未来网络前瞻性研究基金资助项目;The Future Networks Prospective Research Program of Jiangsu Province(BY2013095-2-06)
- DOI：10.11959/j.issn.1000-436x.2015055
  中图分类号： TP393
- 网络出版日期：2015-03，
  
  纸质出版日期：2015-03-25
- 稿件说明：
移动端阅览
黄永锋, 董永强, 张三峰, 等. 基于社会特征周期演化的机会移动网络路由转发策略[J]. 通信学报, 2015,36(3):21-32.

Yong-feng HUANG, Yong-qiang DONG, San-feng ZHANG, et al. Message forwarding based on periodically evolving social characteristics in opportunistic mobile networks[J]. Journal of communications, 2015, 36(3): 21-32.
黄永锋, 董永强, 张三峰, 等. 基于社会特征周期演化的机会移动网络路由转发策略[J]. 通信学报, 2015,36(3):21-32. DOI： 10.11959/j.issn.1000-436x.2015055.

Yong-feng HUANG, Yong-qiang DONG, San-feng ZHANG, et al. Message forwarding based on periodically evolving social characteristics in opportunistic mobile networks[J]. Journal of communications, 2015, 36(3): 21-32. DOI： 10.11959/j.issn.1000-436x.2015055.

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。

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.

关键词

Keywords

references

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