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Minimising collisions in RFID data streams using probabilistic Cluster-Based Technique

机译:使用基于机群的概率技术使RFID数据流中的冲突最小化

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Radio Frequency Identification (RFID) uses wireless radio frequency technology to automatically identify tagged objects. Despite the extensive development of the RFID technology in many areas, tags collisions still remain a major problem. This issue is known as the collision problem and can be solved by using anti-collision techniques. Current probabilistic anti-collision approaches suffer from tag starvation due to the inaccurate Backlog estimation and have a low performance in some cases. In this research, we propose a Probabilistic Cluster-Based Technique (PCT) to maximise the performance efficiency during the tag identification process. The PCT approach creates new tag grouping strategies using particular equations, according to the optimal efficiency obtained for a specific number of tags. Through extensive experimentation, we have demonstrated that the proposed concept performs better than the other current state-of-the-art approaches.
机译:射频识别(RFID)使用无线射频技术来自动识别标记的对象。尽管RFID技术在许多领域得到了广泛的发展,但标签碰撞仍然是一个主要问题。此问题称为碰撞问题,可以使用防碰撞技术解决。由于不正确的积压估计,当前的概率防冲突方法遭受标签匮乏的困扰,并且在某些情况下性能低下。在这项研究中,我们提出了一种基于概率聚类的技术(PCT),以在标签识别过程中最大化性能效率。 PCT方法根据为特定数量的标签获得的最佳效率,使用特定的公式创建新的标签分组策略。通过广泛的实验,我们证明了所提出的概念比其他当前最新技术方法具有更好的性能。

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