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SRMM: A Social Relationship-Aware Human Mobility Model

机译：SRMM：社会关系感知人类流动模型

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摘要

Since human movement patterns are important for validating the performance of wireless networks, several traces of human movements in real life have been collected. However, collecting data about human movements is costly and time-consuming. Moreover, multiple traces are demanded to test various network scenarios. As a result, a lot of synthetic models of human movement have been proposed. Nevertheless, most of the proposed models were often based on random generation, and cannot produce realistic human movements. Although there have been a few models that tried to capture the characteristics of human movement in real life (e.g., flights, inter-contact times, and pause times following the truncated power-law distribution), those models still cannot reflect realistic human movements due to a lack of consideration for social context among people. To address those limitations, in this paper, we propose a novel human mobility model called the social relationship-aware human mobility model (SRMM), which considers social context as well as the characteristics of human movement. SRMM partitions people into social groups by exploiting information from a social graph. Then, the movements of people are determined by considering the distances to places and social relationships. The proposed model is first evaluated by using a synthetic map, and then a real road map is considered. The results of SRMM are compared with a real trace and other synthetic mobility models. The obtained results indicate that SRMM is consistently better at reflecting both human movement characteristics and social relationships.
机译：由于人类运动模式对于验证无线网络性能很重要，因此已经收集了现实生活中的几种人类运动痕迹。但是，收集有关人类运动的数据是昂贵和耗时的。此外，需要多个跟踪来测试各种网络方案。结果，已经提出了许多人体运动的合成模型。然而，大多数拟议的模型通常基于随机产生，不能产生现实的人类运动。虽然有一些模特试图在现实生活中捕捉人类运动的特征（例如，航班，接触时间和截断的幂律分布后的暂停时间），但这些模型仍然无法反映出逼真的人类运动缺乏人们之间的社会环境缺乏考虑。为了解决这些限制，在本文中，我们提出了一种称为社会关系感知人类流动模型（SRMM）的新型人类流动模型，其认为社会背景以及人类运动的特征。 SRMM通过从社会图中剥削信息来将人们分解为社会群体。然后，通过考虑到地点和社会关系的距离来确定人们的运动。首先通过使用合成图评估所提出的模型，然后考虑真正的路线图。 SRMM的结果与实际轨迹和其他合成移动模型进行比较。所获得的结果表明，SRMM在反映人类运动特征和社会关系方面始终如一。

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