Using mobile node speed changes for movement direction change prediction in a realistic category of mobility models
Using mobile node speed changes for movement direction change prediction in a realistic category of mobility models
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DOI：
10.1016/j.jnca.2013.01.012
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发表时间：
2013-05
期刊：
影响因子：
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通讯作者：
Masoud Zarifneshat;P. Khadivi
中科院分区：
文献类型：
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作者：
Masoud Zarifneshat;P. Khadivi
为了评估Ad Hoc网络协议的性能，必须在实际条件下对协议进行测试。这些条件可以包括合理的传输范围、有限的缓冲器大小和移动的用户的实际移动（移动性模型）。在本文中，我们提出了一种新的和现实类型的随机移动模型中，移动的节点必须减速，以达到点的方向变化和加速与定义的加速度，以达到其预期的速度。这种现实的移动性模型提出了基于随机移动性模型。实际上，移动的对象在它们将要改变它们的方向时倾向于改变它们的速度，即，在接近方向改变点时减速，并且在它们开始在新的方向上移动时加速。因此，在本文中，我们实现这种行为的随机移动模型，缺乏这样的规范。事实上，本文代表了我们的努力，使用这种加速的运动，以合理的信心来预测一个移动的节点可能的方向变化。本文的模拟类型是基于流动性轨迹生成器工具产生的轨迹。我们使用一个数据挖掘的概念，称为关联规则挖掘，以找到任何可能的相关性加速移动的移动的节点和概率，移动的节点要改变其方向。我们计算了这个问题的置信度和提升参数，并基于随机移动模型模拟了这个移动模型。这些模拟显示了加速运动的发生和移动的节点的方向改变的事件之间的有意义的相关性。
In order to evaluate performance of protocols for ad hoc networks, the protocols have to be tested under realistic conditions. These conditions may include a reasonable transmission range, a limited buffer size, and realistic movement of mobile users (mobility models). In this paper, we propose a new and realistic type of random mobility models in which the mobile node has to decelerate to reach the point of direction change and accelerates with a defined acceleration to reach its intended speed. This realistic mobility model is proposed based on random mobility models. In reality, mobile objects tend to change their speed when they are going to change their direction, i.e. decelerate when approaching a direction change point and accelerate when they start their movement in a new direction. Therefore, in this paper, we implement this behavior in random mobility models which lack such specification. In fact, this paper represents our effort to use this accelerated movement to anticipate a probable direction change of a mobile node with reasonable confidence. The simulation type of this paper is based on traces produced by a mobility trace generator tool. We use a data mining concept called association rule mining to find any possible correlations between accelerated movement of mobile node and the probability that mobile node wants to change its direction. We calculate confidence and lift parameters for this matter, and simulate this mobility model based on random mobility models. These simulations show a meaningful correlation between occurrence of an accelerated movement and event of mobile node's direction change.