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Efficient Routing Algorithms Combining History and Social Predictors in Mobile Social Networks

机译:移动社交网络中结合历史和社交预测因素的高效路由算法

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A mobile Social Network (MSN) is a type of wireless networks formed by people moving around carrying mobile devices. In this paper, we specifically study the MSNs that are formed impromptu, e.g. when people gather together for a conference, event, or festival. We refer to them as Impromptu Mobile Social Networks (IMSNs), which allow people to communicate in a lightweight fashion based on contact opportunities via local wireless bandwidth. In IMSNs, node connections are time-dependent and short-term. The existing MSN routing algorithms using network analysis of social network graphs and static node social features may not be suitable for IMSNs. Thus, we propose novel hybrid routing algorithms based on two time-related factors node contact history and dynamic social features to capture node mobility in IMSNs. We first propose a hybrid algorithm called Hisso that makes a weighted combination of the history and the social predictors based on these two factors. And then we upgrade it to Enhanced Hisso by introducing a novel concept called social circle in the social predictor to improve message delivery. Simulation results comparing our algorithms with the existing ones and with the ones that only consider one factor show that our algorithms outperform the others in terms of delivery ratio and latency with a slight increase in the number of forwardings. The results also confirm the effectiveness of using a node's social circle in our algorithms.
机译:移动社交网络(MSN)是一种由人们随身携带移动设备而形成的无线网络。在本文中,我们专门研究即兴形成的MSN。人们聚集在一起参加会议,活动或节日时。我们称它们为即兴移动社交网络(IMSN),它使人们可以根据联系机会通过本地无线带宽以轻量级方式进行通信。在IMSN中,节点连接是时间相关的且是短期的。使用社交网络图和静态节点社交功能的网络分析的现有MSN路由算法可能不适合IMSN。因此,我们提出了基于两个时间相关因素的节点接触历史和动态社交特征的新颖混合路由算法,以捕获IMSN中的节点移动性。我们首先提出一种称为Hisso的混合算法,该算法基于这两个因素对历史和社会预测因子进行加权组合。然后,我们通过在社交预测器中引入一种称为社交圈的新概念来将其升级为增强型Hisso,以改善消息传递。仿真结果将我们的算法与现有算法以及仅考虑一个因素的算法进行了比较,结果表明,我们的算法在传输率和延迟方面优于其他算法,转发数量略有增加。结果还证实了在我们的算法中使用节点的社交圈的有效性。

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