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

机译:识别& 衡量社会关系:基于社会关系的机遇网络中的路由算法

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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:识别和衡量社会关系已被提出作为机会网络中信息路由的方法。 在本文中,我们设计了一种基于社会关系的路由算法(SRBRA),其克服了现有识别和测量社交关系算法中的常见问题,例如测量参数的缺陷以及应用域的限制使用。 首先,通过从网络中的移动节点分析实时数据,我们总结并提取影响这些移动节点之间的社会关系的因素。 然后对来自多个角度的这些因素的复杂性和动态进行推断和评估,计算来自这些因素的每个传感器节点之间的社会关系值。 最后,基于社会关系的价值,我们整理了邻居的网络拓扑信息,并选择用于信息路由的最佳巢跳中继节点。 仿真实验表明,SRBRA是具有成本效益并且具有高的输送率。

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