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在时间受限的 RFID 配置中对标记集的最优识别。

On the optimal identification of tag sets in time-constrained RFID configurations.

机构信息

Department of Information Technologies and Communications, Technical University of Cartagena, Plaza del Hospital 1, 30202 Cartagena, Spain.

出版信息

Sensors (Basel). 2011;11(3):2946-60. doi: 10.3390/s110302946. Epub 2011 Mar 4.

DOI:10.3390/s110302946
PMID:22163777
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3231632/
Abstract

In Radio Frequency Identification facilities the identification delay of a set of tags is mainly caused by the random access nature of the reading protocol, yielding a random identification time of the set of tags. In this paper, the cumulative distribution function of the identification time is evaluated using a discrete time Markov chain for single-set time-constrained passive RFID systems, namely those ones where a single group of tags is assumed to be in the reading area and only for a bounded time (sojourn time) before leaving. In these scenarios some tags in a set may leave the reader coverage area unidentified. The probability of this event is obtained from the cumulative distribution function of the identification time as a function of the sojourn time. This result provides a suitable criterion to minimize the probability of losing tags. Besides, an identification strategy based on splitting the set of tags in smaller subsets is also considered. Results demonstrate that there are optimal splitting configurations that reduce the overall identification time while keeping the same probability of losing tags.

摘要

在射频识别(RFID)设施中,一组标签的识别延迟主要是由读取协议的随机访问性质引起的,从而导致一组标签的随机识别时间。在本文中,使用离散时间马尔可夫链评估了单组时间受限无源 RFID 系统(即仅假设一组标签在读取区域内且在离开前有一个有限的时间(逗留时间))的识别时间的累积分布函数。在这些场景中,一组中的某些标签可能无法被识别。该事件的概率可以从识别时间的累积分布函数中获得,该函数是逗留时间的函数。该结果提供了一个合适的标准来最小化标签丢失的概率。此外,还考虑了一种基于将标签集划分为更小子集的识别策略。结果表明,存在最优的划分配置,可以在保持相同标签丢失概率的情况下减少整体识别时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/d970f1f7a305/sensors-11-02946f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/fee1fe0aab88/sensors-11-02946f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/49f080d56199/sensors-11-02946f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/b91119466d16/sensors-11-02946f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/b2fa715e119e/sensors-11-02946f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/658abc6fea68/sensors-11-02946f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/fb2a9ecbecba/sensors-11-02946f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/c8821b88e41a/sensors-11-02946f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/735c7ac1e62b/sensors-11-02946f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/6205c7b4e44c/sensors-11-02946f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/d970f1f7a305/sensors-11-02946f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/fee1fe0aab88/sensors-11-02946f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/49f080d56199/sensors-11-02946f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/b91119466d16/sensors-11-02946f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/b2fa715e119e/sensors-11-02946f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/658abc6fea68/sensors-11-02946f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/fb2a9ecbecba/sensors-11-02946f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/c8821b88e41a/sensors-11-02946f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/735c7ac1e62b/sensors-11-02946f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/6205c7b4e44c/sensors-11-02946f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8fb/3231632/d970f1f7a305/sensors-11-02946f10.jpg

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