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Implementation of Differential Tag Sampling for COTS RFID Systems

机译:COTS RFID系统的差分标签采样的实现

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Tag inventory is one of the most fundamental tasks for RFID systems. However, the Framed Slotted Aloha (FSA) protocol specified in the C1G2 standard is of low time-efficiency, because it needs to collect all tags in the system. To improve time-efficiency, research communities proposed a batch of sampling-based approaches, in which the reader only needs to collect a small set of sampled tags instead of all. Although time-efficiency has been improved, existing sampling-based approaches still have two common limitations. First, all tags in the system are assumed to have the same sampling probability. It is unfair that tags attached to differential items (e.g., different values) have the same chance to be sampled and collected. Second, all existing sampling-based approaches stay in theory level and cannot be deployed on Commercial Off-The-Shelf (COTS) RFID devices, because the C1G2 standard does not support the sampling function at all. To deal with the above two limitations, this paper studies the new problem of differential tag sampling-letting each RFID tag be identified with a given sampling probability. In this paper, we use the COTS RFID devices including Impinj Speedway R420 reader and Monza 4QT tags to implement the Differential Tag Sampling (DTS) operation. Then, we apply probabilistic analytics on the collected tag data to address some practically important problems such as Multi-category Tag Cardinality Estimation (MTCE), and Value-based Missing Tag Detection (VMTD). Although the analytics results are not 100 percent accurate, the deviation in the results can be controlled below a small threshold and DTS can significantly improve the time-efficiency. DTS can be easily deployed on the COTS RFID systems, because it is totally compliant with the C1G2 standard. Extensive experiments demonstrate that DTS is able to let each tag take the given sampling probability to be sampled and identified. Moreover, the proposed DTS protocol can significantly reduce the execution time of MTCE and VMTD by nearly 70 percent than the FSA protocol.
机译:标签库存是RFID系统最基本的任务之一。然而,C1G2标准中规定的框架的开槽Aloha(FSA)协议具有低时间效率,因为它需要收集系统中的所有标签。为了提高时间效率,研究社区提出了一批基于采样的方法,其中读者只需要收集一组小型采样标签而不是全部采样。虽然时间效率已经提高,但现有的基于样品的方法仍然有两个常见限制。首先,假设系统中的所有标记具有相同的采样概率。它是不公平的,附加到差异项目(例如,不同的值)的标签具有相同的方法可以采样和收集。其次,所有现有的基于采样的方法都保持在理论水平,无法部署在商业现成(COTS)RFID设备上,因为C1G2标准根本不支持采样功能。为了处理上述两个限制,本文研究了采样的差分标签的新问题 - 让每个RFID标签用给定采样概率识别。在本文中,我们使用COTS RFID设备,包括Impinj Speedway R420 Reader和Monza 4QT标签,以实现差分标签采样(DTS)操作。然后,我们在收集的标签数据上应用概率分析,以解决一些实际上重要的问题,例如多类别标签基数估计(MTCE)和基于价值的缺失标签检测(VMTD)。虽然分析结果不是100%准确,但结果的偏差可以控制在小阈值以下,并且DTS可以显着提高时间效率。可以轻松地部署在COTS RFID系统上,因为它完全符合C1G2标准。大量实验表明,DTS能够让每个标签采取给定的采样概率进行采样和识别。此外,所提出的DTS协议可以显着降低MTCE和VMTD的执行时间,而不是FSA协议的近70%。

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