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

被引：2

作者：

Huang, Yong-Feng ^{[1
]}

Dong, Yong-Qiang ^{[1
,2
]}

Zhang, San-Feng ^{[1
,2
]}

Wu, Guo-Xin ^{[1
,2
]}

机构：

[1] School of Computer Science and Engineering, Southeast University, Nanjing

[2] Key Laboratory of Computer Network and Information Integration, Ministry of Education, Southeast University, Nanjing

来源：

Tongxin Xuebao/Journal on Communications | 2015年 / 36卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Centrality; Community; Message forwarding; Opportunistic mobile networks; Periodic evolution;

D O I：

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

中图分类号：

学科分类号：

摘要：

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 keeping similar routing overhead. ©, 2015, Tongxin Xuebao/Journal on Communications. All right reserved.

引用

页数：12

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