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Cardinality Estimation for Large-Scale RFID Systems

机译:大型RFID系统的基数估计

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Counting the number of RFID tags (cardinality) is a fundamental problem for large-scale RFID systems. Not only does it satisfy some real application requirements, it also acts as an important aid for RFID identification. Due to the extremely long processing time, slotted ALOHA-based or tree-based arbitration protocols are often impractical for many applications, because tags are usually attached to moving objects and they may have left the readers interrogation region before being counted. Recently, estimation schemes have been proposed to count the approximate number of tags. Most of them, however, suffer from two scalability problems: time inefficiency and multiple-reading. Without resolving these problems, large-scale RFID systems cannot easily apply the estimation scheme as well as the corresponding identification. In this paper, we present the Lottery Frame (LoF) estimation scheme, which can achieve high accuracy, low latency, and scalability. LoF estimates the tag numbers by utilizing the collision information. We show the significant advantages, e.g., high accuracy, short processing time, and low overhead, of the proposed LoF scheme through analysis and simulations.
机译:计算RFID标签的数量(基数)是大规模RFID系统的基本问题。它不仅可以满足某些实际应用需求,而且还可以作为RFID识别的重要辅助工具。由于处理时间非常长,基于时隙的基于ALOHA或基于树的仲裁协议对于许多应用程序通常是不切实际的,因为标签通常附着在移动的对象上,并且在被计数之前可能已离开读取器询问区域。最近,已经提出了估计方案以对标签的近似数量进行计数。但是,它们中的大多数都存在两个可伸缩性问题:时间效率低下和多次读取。如果不解决这些问题,大规模的RFID系统将无法轻松地应用估计方案以及相应的标识。在本文中,我们提出了一种彩票框架(LoF)估计方案,该方案可以实现高精度,低延迟和可伸缩性。 LoF通过利用冲突信息来估计标签号。我们通过分析和仿真显示了拟议的LoF方案的显着优势,例如高精度,短处理时间和低开销。

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