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大规模射频识别系统中最值的最短时间估计算法

Minimum Time Extrema Estimation for Large-Scale Radio-Frequency Identification Systems

  • 摘要: 针对由上千个标签构成的射频识别系统中的最值估计问题,设计耗时最短的最值估计协议,以在最短的时间内同时准确估计射频识别系统的最大值和最小值。
    分析导致经典二分查找协议耗时较长的原因,发现该协议广播了大量时间帧,而每两帧之间有额外的帧间开销。据此,提出了一个参数化协议,将帧的长度设置为参数,推导出总耗时和帧长度之间的关系,然后寻找最优的帧长度。在此基础上进一步优化了协议。第一个优化是寻找并去除冗余的帧。第二个优化是将估计最小值的帧和估计最大值的帧两两拼接从而减少帧的数量。
    模拟实验表明,标签值的范围以及帧间间隙的长度对协议的耗时有显著的影响。在所有的模拟实验中,提出协议的耗时均小于经典的二分查找协议。在典型的设置下,提出协议相对于经典二分查找协议耗时减少了79%。
    未来计划研究标签动态改变值的场景,即如何跟踪估计标签系统的最值。

     

    Abstract: We consider the extrema estimation problem in large-scale radio-frequency identification (RFID) systems, where there are thousands of tags and each tag contains a finite value. The objective is to design an extrema estimation protocol with the minimum execution time. Because the standard binary search protocol wastes much time due to interframe overhead, we propose a parameterized protocol and treat the number of slots in a frame as an unknown parameter. We formulate the problem and show how to find the best parameter to minimize the worst-case execution time. Finally, we propose two rules to further reduce the execution time. The first is to find and remove redundant frames. The second is to concatenate a frame from minimum value estimation with a frame from maximum value estimation to reduce the total number of frames. Simulations show that, in a typical scenario, the proposed protocol reduces execution time by 79% compared with the standard binary search protocol.

     

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