| 摘要: |
| 移动社会网络是一种由大量具有社会特征的节点组成的机会网络.已有的基于社区的路由算法大多选用社会性最优的节点参与转发,而没有考虑到社区分布对节点移动的影响,将这些算法直接用于移动社会网络中会导致网络资源消耗高、传输成功率低等问题.针对这些问题,提出一种基于社区的消息机会传输算法,在社区间根据节点到目标社区的传输概率选择社区间的最优传输路径,在社区内选择与目标节点相遇概率较高的节点完成社区内传输.仿真实验结果表明,在移动社会网络中,该算法与 Prophet,Spray and Wait 等经典算法相比,提高了消息传输成功率,降低了网络开销. |
| 关键词: 移动社会网络 社区特性 消息转发 传输概率 相遇概率 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金(61162002,61364023);江西省自然科学基金(20151BAB207038) |
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| Community-Based Message Opportunistic Transmission Scheme in Mobile Social Networks |
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ZHANG Sheng1, LIU Xiao-Dong1, BAO Xiao-Ling2, GUO Shui-Ying1, WANG Xin1
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1.School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China;2.School of Foreign Language, Nanchang Hangkong University, Nanchang 330063, China
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| Abstract: |
| Mobile social network is a kind of opportunistic networks composed of a large number of nodes with social characteristic. However the prevalent community-based routing mostly chooses nodes that have optimal social characteristic to transmit messages, without considering the distribution of communities. Hense these algorithms usually result in high consumption of cyber resource and low transmission success when deployed directly in mobile social networks. To tackle these problems, this study proposes a community-based message opportunistic transmission algorithm(CMOT). For intra-community communication, CMOT chooses an optimal path for message transmission from local community to target community by comparing the transmission probability between the nodes. For inter-community messages transmission, CMOT chooses an optimal community path by comparing the community transmission probability. For intra-community in local community, messages are forwarded according to the encounter probability between nodes. The simulation results show that, compared with classical routing algorithms, such as PRoPHET, MaxProp, Spray and Wait, and CMTS, CMOT improves the successful message delivery ratio and evidently reduces network overhead. |
| Key words: mobile social network community characteristic message forwarding transmission probability encounter probability |
