학술논문

Collisions Are Preferred: RFID-Based Stocktaking with a High Missing Rate
Document Type
Periodical
Source
IEEE Transactions on Mobile Computing IEEE Trans. on Mobile Comput. Mobile Computing, IEEE Transactions on. 19(7):1544-1554 Jul, 2020
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Libraries
Heuristic algorithms
Adaptation models
RFID tags
Mobile computing
Approximation algorithms
RFID
stocktaking
time efficiency
missing rate
CLS
DLS
Language
ISSN
1536-1233
1558-0660
2161-9875
Abstract
RFID-based stocktaking uses RFID technology to verify the presence of objects in a region e.g., a warehouse or a library, compared with an inventory list. The existing approaches for this purpose assume that the number of missing tags is small. This is not true in some cases. For example, for a handheld RFID reader, only the objects in a larger region (e.g., the warehouse) rather than in its interrogation region can be known as the inventory list, and hence many tags in the list are regarded as missing. The missing objects significantly increase the time required for stocktaking. In this paper, we propose an algorithm called CLS (Coarse-grained inventory list based stocktaking) to solve this problem. CLS enables multiple missing objects to hash to a single time slot and thus verifies them together. CLS also improves the existing approaches by utilizing more kinds of RFID collisions and reducing approximately one-fourth of the amount of data sent by the reader. Moreover, we observe that the missing rate constantly changes during the identification because some of tags are verified present or absent, which affects time efficiency; accordingly, we propose a hybrid stocktaking algorithm called DLS (Dynamic inventory list based stocktaking) to adapt to such changes for the first time. According to the results of extensive simulations, when the inventory list is 20 times that of actually present tags, the execution time of our approach is 36.3 percent that of the best existing algorithm.