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Identify Measure Social Relations: Routing Algorithm Based on Social Relations in Opportunistic Networks

机译:识别和衡量社会关系:机会网络中基于社会关系的路由算法

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摘要

Identify & measure social relations has been proposed as a method for information routing in opportunistic networks. In this paper, we design a social-relations-based routing algorithm (SRBRA), which overcomes the common issues in existing identify &measure social relation algorithms, such as the deficiency of measuring parameters and the restrict usage of application domain. Firstly, by analyzing the real-time data from mobile nodes in the network, we summarize and extract factors that affect social relations between these mobile nodes. Then make inference and evaluation for the complexity and dynamic of these factors from multiple angles, calculate the social-relations values between each sensor node from these factors. Finally, based on the values of social relations, we sort out the network topology information of the neighbors, and select the best nest hop relay node for information routing. Simulation experiments show that SRBRA is cost effective and has high delivery ratio.
机译:已经提出了识别和测量社会关系作为机会网络中信息路由的方法。本文设计了一种基于社会关系的路由算法(SRBRA),该算法克服了现有的识别与测量社会关系算法中存在的普遍性问题,即测量参数的不足和应用领域的限制使用。首先,通过分析来自网络中移动节点的实时数据,我们总结并提取了影响这些移动节点之间社会关系的因素。然后从多个角度对这些因素的复杂性和动态性进行推断和评估,并根据这些因素计算每个传感器节点之间的社会关系值。最后,根据社会关系的价值,对邻居的网络拓扑信息进行分类,并选择最佳的嵌套跳中继节点进行信息路由。仿真实验表明,SRBRA具有较高的性价比,并且具有很高的交付率。

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