Minimum Time Extrema Estimation for Large-Scale Radio-Frequency Identification Systems
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Minimum Time Extrema Estimation for Large-Scale Radio-Frequency Identification Systems Xiao-Jun Zhu1,2 , Member, CCF, IEEE, Li-Jie Xu2 , Xiao-Bing Wu3 , and Bing Chen1 , Senior Member, CCF 1
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2
Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing 210049, China
3
Wireless Research Centre, University of Canterbury, Christchurch 8041, New Zealand
E-mail: [email protected]; [email protected]; [email protected]; cb [email protected] Received July 9, 2019; revised March 14, 2020. 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. Keywords radio-frequency identification (RFID) system, maximum value estimation, minimum value estimation, time efficient protocol
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Introduction
In some radio-frequency identification (RFID) systems, RFID tags can carry values that are sensed from the environment [1] . For example, a tag can be affiliated with a thermometer to monitor temperatures. We are interested in estimating the maximum and the minimum values, which are useful in scenarios such as temperature monitoring applications in museums. In these systems, the minimum and the maximum temperatures are related to whether the protected heritage will be ruined. We formulate the problem to minimize the time to estimate the extrema. One approach is to require tags to return their val-
ues similar to tag identification [2–5] . Though this can give accurate statistics, the consumed time is proportional to the number of tags, which is not affordable in large-scale RFID systems. Researchers propose efficient protocols to reduce the time for estimating the statistics, e.g., the median value [6] or the histogram [7] . Another approach is to repeatedly ask whether a candidate value is the minimum (or the maximum), followed by adjusting values in a binary search framework. In particular, the reader broadcasts a candidate value and requests tags with smaller values to respond. If some tag responds (i.e., the reader dete
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