Radio frequency identification (RFID) technology has been widely used in missing tag detection to reduce and avoid inventory shrinkage. In this application, promptly finding out the missing event is of paramount importance. However, existing missing tag detection protocols cannot efficiently handle the presence of a large number of unexpected tags whose IDs are not known to the reader, which shackles the time efficiency. To deal with the problem of detecting missing tags in the presence of unexpected tags, this paper introduces a two-phase Bloom filter-based missing tag detection protocol (BMTD). The proposed BMTD exploits Bloom filter in sequence to first deactivate the unexpected tags and then test the membership of the expected tags, thus dampening the interference from the unexpected tags and considerably reducing the detection time. Moreover, the theoretical analysis of the protocol parameters is performed to minimize the detection time of the proposed BMTD and achieve the required reliability simultaneously. Extensive experiments are then conducted to evaluate the performance of the proposed BMTD. The results demonstrate that the proposed BMTD significantly outperforms the state-of-the-art solutions.
Radio Frequency Identification (RFID) technology has been widely used in inventory management in many scenarios, e.g., warehouses, retail stores, hospitals, etc. This paper investigates a challenging problem of complete identification of missing tags in large-scale RFID systems. Although this problem has attracted extensive attention from academy and industry, the existing work can hardly satisfy the stringent real-time requirements. In this paper, a Slot Filter-based Missing Tag Identification (SFMTI) protocol is proposed to reconcile some expected collision slots into singleton slots and filter out the expected empty slots as well as the unreconcilable collision slots, thereby achieving the improved time-efficiency. The theoretical analysis is conducted to minimize the execution time of the proposed SFMTI. We then propose a cost-effective method to extend SFMTI to the multi-reader scenarios. The extensive simulation experiments and performance results demonstrate that the proposed SFMTI protocol outperforms the most promising Iterative ID-free Protocol (IIP) by reducing nearly 45 of the required execution time, and is just within a factor of 1.18 from the lower bound of the minimum execution time. Radio frequency identification (RFID) technologies are poised to revolutionize retail, warehouse, and supply chain management. One of their interesting applications is to automatically detect missing tags in a large storage space, which may have to be performed frequently to catch any missing event such as theft in time. Because RFID systems typically work under low-rate channels, past research has focused on reducing execution time of a detection protocol to prevent excessively long protocol execution from interfering normal inventory operations. However, when active tags are used for a large spatial coverage, energy efficiency becomes critical in prolonging the lifetime of these battery-powered tags. Furthermore, much of the existing literature assumes that the channel between a reader and tags is reliable, which is not always true in reality because of noise interference in the environment. Given these concerns, this paper makes three contributions. First, we propose a novel protocol design that considers both energy efficiency and time efficiency. It achieves multifold reduction in both energy cost and execution time when compared to the best existing work. Second, we reveal a fundamental energy-time tradeoff in missing-tag detection, which can be flexibly controlled through a couple of system parameters in order to achieve desirable performance. Third, we extend our protocol design to consider channel error under two different models. We find that energy time cost will be higher in unreliable channel conditions, but the energy-time tradeoff relation persists. RFID (radio-frequency identification) is an emerging technology with extensive applications such as transportation and logistics, object tracking, and inventory management. How to quickly identify the missing RFID tags and thus their associated objects is a practically important problem in many large-scale RFID systems. This paper presents three novel methods to quickly identify the missing tags in a large-scale RFID system of thousands of tags. Our protocols can reduce the time for identifying all the missing tags by up to 75 in comparison to the state of art. RFID (radio frequency identification) technologies are poised to revolutionize retail, warehouse and supply chain management. One of their interesting applications is to automatically detect missing tags (and the associated objects) in a large storage space. In order to timely catch any missing event such as theft, the detection operation may have to be performed frequently. Because RFID systems typically work under low-rate channels, past research has focused on reducing execution time of a detection protocol, in order to prevent excessively-long protocol execution from interfering normal inventory operations. However, when active tags are used to provide a large spatial coverage, energy efficiency becomes critical in prolonging the lifetime of these battery-powered tags. Existing literature lacks thorough study on how to conserve energy in the process of missing-tag detection and how to jointly optimize energy efficiency and time efficiency. This paper makes two important contributions: First, we propose a novel protocol design that takes both energy efficiency and time efficiency into consideration. It achieves multi-fold reduction in both energy cost and execution time when comparing with the best existing work. In some cases, the reduction is more than an order of magnitude. Second, we reveal a fundamental energy-time tradeoff in missing-tag detection. Through our analytical framework, we are able to flexibly control the tradeoff through a couple of system parameters in order to achieve desirable performance. As RFID tags become more widespread, new approaches for managing larger numbers of RFID tags will be needed. In this paper, we consider the problem of how to accurately and efficiently monitor a set of RFID tags for missing tags. Our approach accurately monitors a set of tags without collecting IDs from them. It differs from traditional research which focuses on faster ways for collecting IDs from every tag. We present two monitoring protocols, one designed for a trusted reader and another for an untrusted reader. Comparing with the classical barcode system, RFID extends the operational distance from inches to a number of feet (passive RFID tags) or even hundreds of feet (active RFID tags). Their wireless transmission, processing and storage capabilities enable them to support the full automation of many inventory management functions in the industry. This paper studies the practically important problem of monitoring a large set of RFID tags and identifying the missing ones - the objects that the missing tags are associated with are likely to be missing, too. This monitoring function may need to be executed frequently and therefore should be made efficient in terms of execution time, in order to avoid disruption of normal inventory operations. Based on probabilistic methods, we design a series of missing-tag identification protocols that employ novel techniques to reduce the execution time. Our best protocol reduces the time for detecting the missing tags by 88.9 or more, when comparing with existing protocols. RFID systems have been deployed to detect missing products by affixing them with cheap passive RFID tags and monitoring them with RFID readers. Existing missing tag detection protocols require the tag population to contain only those tags whose IDs are already known to the reader. However, in reality, tag populations often contain tags with unknown IDs, called unexpected tags, and cause unexpected false positives i.e., due to them, missing tags are detected as present. We take the first step towards addressing the problem of detecting the missing tags from a population that contains unexpected tags. Our protocol, RUN, mitigates the adverse effects of unexpected false positives by executing multiple frames with different seeds. It minimizes the missing tag detection time by first estimating the number of unexpected tags and then using it along with the false positive probability to obtain optimal frame sizes and number of times Aloha frames should be executed. RUN works with multiple readers with overlapping regions. It is easy to deploy because it is implemented on readers as a software module and does not require modifications to tags or to the communication protocol between tags and readers. We implemented RUN along with four major missing tag detection protocols and the fastest tag ID collection protocol and compared them side-by-side. Our experimental results show that RUN always achieves the required reliability whereas the best existing protocol achieves a maximum reliability of only 67 .