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    李婕, 洪韬, 王兴伟, 黄敏, 郭静. 机会移动社交网络中基于群组构造的数据分发机制[J]. 计算机研究与发展, 2019, 56(11): 2494-2505. DOI: 10.7544/issn1000-1239.2019.20180750
    引用本文: 李婕, 洪韬, 王兴伟, 黄敏, 郭静. 机会移动社交网络中基于群组构造的数据分发机制[J]. 计算机研究与发展, 2019, 56(11): 2494-2505. DOI: 10.7544/issn1000-1239.2019.20180750
    Li Jie, Hong Tao, Wang Xingwei, Huang Min, Guo Jing. A Data Dissemination Mechanism Based on Group Structure in Opportunistic Mobile Social Networks[J]. Journal of Computer Research and Development, 2019, 56(11): 2494-2505. DOI: 10.7544/issn1000-1239.2019.20180750
    Citation: Li Jie, Hong Tao, Wang Xingwei, Huang Min, Guo Jing. A Data Dissemination Mechanism Based on Group Structure in Opportunistic Mobile Social Networks[J]. Journal of Computer Research and Development, 2019, 56(11): 2494-2505. DOI: 10.7544/issn1000-1239.2019.20180750

    机会移动社交网络中基于群组构造的数据分发机制

    A Data Dissemination Mechanism Based on Group Structure in Opportunistic Mobile Social Networks

    • 摘要: 机会移动社交网络(opportunistic mobile social networks, OMSNs)是一种利用节点的相遇机会进行端到端无线数据传输的网络.随着人们使用移动智能终端数量的剧增,为建立泛在的数据传输基础设施提供了机会,因此研究机会移动社交网络的数据传输机制具有重要意义.为了提高机会移动社交网络的数据传输性能,提出了一种基于群组构造的数据分发机制(data dissemination mechanism based on group structure, DDMGS).首先,基于用户的行为属性,即节点重要性、兴趣相似度和通信关系紧密度,设计关系度量模型.其次,依据不同的行为属性关系构成的网络拓扑特征设计群组构造算法:基于位置关系的拓扑结构具有周期稳定性,基于兴趣关系的拓扑结构具有长期稳定性,而基于通信关系的拓扑结构具有动态性.为进一步提高数据分发性能和网络的整体性能,还设计了节点缓冲区管理机制,引入了合作博弈理论加强节点之间的合作能力,规避节点的自私行为.仿真验证表明DDMGS与直接投递路由、先知路由以及Simbet路由和Epidemic路由相比具有较好的性能,提高了消息传输成功率,减少了平均跳数,该算法是可行的.

       

      Abstract: Opportunistic mobile social networks (OMSNs) are the network where mobile users utilize opportunistic contacts to transmit data by wireless peer-to-peer interaction. The growing share of using smart mobile devices offers the opportunity to build a ubiquitous infrastructure for data disseminations, so it is significant to study data transmissions in OMSNs. In order to improve the data dissemination performance of OMSNs, a data dissemination mechanism based on group structure (DDMGS) is proposed in this paper. Firstly, the relationship measurement model is designed based on the user’s behavior attributes that include the user’s movement trajectories, interests and communication behaviors. In addition, the group construction algorithm is designed for network topology composed of different behavior attribute relations. The topological structure based on location relationship has periodic stability. The topological structure based on interest relationship has long-term stability. The topological structure based on communication relationship has dynamicity. In order to improve the data dissemination performance and the overall network performance, a buffer management scheme is designed, and a cooperative game theory is introduced to strengthen the cooperation between nodes, to avoid the selfish behavior of the node. Simulation results show that, compared with the performance of direct delivery routing, prophetic routing, Simbet routing and Epidex routing, DDMGS has better performance in success rate of message transmission and the average hop count. It demonstrates that DDMGS is feasible and effective.

       

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