TRAILS - A Trace-Based Probabilistic Mobility Model

Anna Förster, Anas Bin Muslim, A. Udugama
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引用次数: 14

Abstract

Modeling mobility is a key aspect when simulating different types of networks. To cater to this requirement, a large number of models has emerged in the last years. They are typically (a) trace-based, where GPS recordings are re-run in simulation, (b) synthetic models, which describe mobility with formal methods, or (c) hybrid models, which are synthetic models based on statistically evaluated traces. All these families of models have advantages and disadvantages. For example, trace-based models are very inflexible in terms of simulation scenarios, but have realistic behaviour, while synthetic models are very flexible, but lack realism. In this paper, we propose a new mobility model, called TRAILS (TRAce-based ProbabILiStic Mobility Model), which bridges the gap between these families and combines their advantages into a single model. The main idea is to extract a mobility graph from real traces and to use it in simulation to create scalable, flexible simulation scenarios. We show that TRAILS is more realistic than synthetic models, while achieving full scalability and flexibility. We have implemented and evaluated TRAILS in the OMNeT++ simulation framework.
TRAILS -基于跟踪的概率迁移模型
在模拟不同类型的网络时,移动性建模是一个关键方面。为了满足这一需求,在过去的几年里出现了大量的模型。它们通常是(a)基于轨迹,在模拟中重新运行GPS记录,(b)合成模型,用正式方法描述机动性,或(c)混合模型,这是基于统计评估轨迹的合成模型。所有这些模型家族都有优点和缺点。例如,基于追踪的模型在模拟场景方面非常不灵活,但具有逼真的行为,而合成模型非常灵活,但缺乏现实性。在本文中,我们提出了一种新的流动性模型,称为TRAILS (TRAce-based ProbabILiStic mobility model),它弥合了这些家庭之间的差距,并将它们的优势整合到一个单一的模型中。主要思想是从真实的轨迹中提取移动图,并在仿真中使用它来创建可扩展的、灵活的仿真场景。我们证明TRAILS比合成模型更真实,同时实现了充分的可扩展性和灵活性。我们已经在omnet++仿真框架中实现并评估了TRAILS。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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