A cardinality estimation scheme for the number of unknown RFID tags under unreliable channels

In RFID systems, if two or more tags response a reader simultaneously, communication conflict or data interference (i.e. reader collision and/or tag collision) will occur. As a result, the reader cannot receive information of these tags correctly. In order to solve this type of tag collision problem, many tag anti-collision algorithms have been proposed, such as a series of Aloha-based algorithms and their varieties. As one of representatives of Aloha-based algorithms family, Dynamic Frame Slotted Aloha Algorithm (DFSA) is capable of changing the number of slots in a single frame dynamically according to the collision situation in the previous frame. When the number of slots in a frame equals the number of unidentified tags, the RFID system will win the best throughput. In this case, tag collision problem is focused on tag estimation. Because that the traditional Tag Estimation Method (TEM) ignores such information as number of empty slots and slots filled with only one tag, this paper proposes an enhanced tag estimation method (ETEM) to improve estimation accuracy. The simulation results indicate that the proposed ETEM algorithm performs better in both identification time and estimation error than the traditional TEM.

Radio-frequency identification (RFID) has been utilized in many applications, such as supply chain and stock management in supermarkets. RFID systems in such practical applications are inherently dynamic because tags may move in and out frequently. One important but challenging problem in such systems is how to estimate the number of dynamic tags fast and reliably. This article proposes effective solutions to this problem, which guarantee the accuracy of estimation and time efficiency. Especially, we want to simultaneously estimate the number of tags that moved out of the system (missing tags) and the number of tags that entered the system (unknown tags) in a specified time interval. We design a novel method called time slot reuse (TSR) that generates two logical frames corresponding to the two types of tags from only one physical frame. Based on TSR, we propose a protocol called SSR that can accurately estimate the number of dynamic tags by using the generated logic frames. However, the performance of SSR degrades significantly when the disparity between the number of the two types of tags is remarkable. We further propose an enhanced version of SSR (ESSR), which overcomes this drawback by partitioning the frame into ranges and mapping different types of tags into different ranges. Rigorous theoretical analysis is performed to tune parameters in SSR and ESSR to minimize the execution time. The simulation results demonstrate up to 80% improvement in time efficiency when compared with state-of-the-art solutions to the same problem. © 2014 IEEE.

Several communication protocols and applications require a node to know how many neighboring nodes exhibiting a certain attribute it has. Conventionally, such neighbor information is obtained by explicit message exchange between nodes, which is reliable but inefficient in densely connected networks in terms of overhead and delay. An alternative approach is to perform an estimation of the neighbor cardinality using probabilistic methods. This paper pursues such an approach by proposing neighbor cardinality estimators that require no coordination among polled nodes but are based on a simple random access scheme with busy tones, where the number of empty slots is exploited to infer about the neighbor cardinality. We compare three estimators with different levels of adaptability and feedback from the query node and discuss their suitability for IEEE 802.11 and low power sensors. Performance is studied in terms of estimation accuracy and delay.

Summary form only given. Experiments on the Zebra generator with LCM (Load Current Multiplier, provides 1.5-1.7 MA) allow for implosions of larger sized wire array loads (including planar wire arrays) than at standard current of 1 MA. Advantages of larger sized planar wire array implosions include enhanced energy coupling to plasmas and better diagnostic access to observable plasma regions. A full set of diagnostics was implemented to study radiation in a broad spectral range from few Å to few hundred Å using PCD, XRD, and EUV detectors, X-ray/EUV spectrometers and X-ray pinhole cameras. In addition, laser shadowgraphy was utilized. In multi-planar wire arrays, two outer wire planes were each 4.9 mm width and made of eight mid-atomic-number (Alumel with 95% of Ni) wires with the inter-row gap increased from 3 or 6 mm (usually used at 1 MA current) up to 9 mm. A central plane located in the middle between the outer planes had empty slots and a few Al wires at the edges. Recently, we have shown that such configuration produces higher linear radiation yield. In the new experiments, the number of empty slots was further increased from 6 up to 10, increasing the gap inside the middle plane from 4.9 to 7.7 mm, respectively. This allows for more independent study of the flows of L-shell Ni plasma (between the outer planes) and K-shell Al plasma (which first fills the gap between the edge wires along the middle plane) and their radiation in space and time. When studying the combined wire arrays before, the time-gated X-ray spectra have always included radiation from both materials, even at early time. In the present work, for the first time we have observed that the K-shell Al radiation was delayed compared to L-shell Ni radiation when the number of empty slots was increased. In addition, the results of another new experiment are presented when a few Al wires on each edge were replaced by a thicker Cu wire to understand their influence on radiation from outer planes.

Radio frequency identification is a wireless communication technology, which enables data gathering and identifies recognition from any tagged object. The number of collisions produced during wireless communication would lead to a variety of problems including unwanted number of iterations and reader-induced idle slots, computational complexity in terms of estimation as well as recognition of the number of tags. In this work, dynamic frame adjustment and optimal splitting are employed together in the proposed algorithm. In the dynamic frame adjustment method, the length of frames is based on the quantity of tags to yield optimal efficiency. The optimal splitting method is conceived with smaller duration of idle slots using an optimal value for splitting level , where (M > 2), to vary slot sizes to get the minimal identification time for the idle slots. The application of the proposed algorithm offers the advantages of not going for the cumbersome estimation of the quantity of tags incurred and the size (number) of tags has no effect on its performance efficiency. Our experiment results show that using the proposed algorithm, the efficiency curve remains constant as the number of tags varies from 50 to 450, resulting in an overall theoretical gain in the efficiency of 0.032 compared to system efficiency of 0.441 and thus outperforming both dynamic binary tree slotted ALOHA (DBTSA) and binary splitting protocols.

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Mobile RFID tag reading with non-overlapping tandem readers on a conveyor belt

Unknown tags appear when tagged objects are newly moved in or wrongly placed in systems. In this paper, we investigate time-efficient protocols for collecting IDs from unknown tags. Consider the influence of unknown tag density on total recognition time, we design a high-density unknown tags identification (HUTI) protocol and a low-density unknown tags identification (LUTI) protocol, which are suitable for dense unknown tags environment and sparse unknown tags environment, respectively. Indicator vectors are constructed to help tags know expected status of selected slots. The difference between the two proposed protocols is the number of indicator vectors to be used. LUTI utilizes two indicator vectors to accurately decide each expected slot status, while HUTI only use one indicator vector to save transmitting time when the number of unknown tags is large. In order to minimize execution time, we conduct investigations on frame length and round count, of which the results are concluded as the optimal setting parameters. Simulation results demonstrate that our protocols outperform related protocols with respect to total execution time.

Cyclic-reservation multiple-access (CRMA) is an access scheme for high-speed local and metropolitan area networks based on folded-bus or dual-bus configurations. CRMA provides high throughput and fairness independent of the network speed or distance. In CRMA, the headend generates reserve commands periodically. Each station may reserve a number of empty slots in each reserve command if necessary. Corresponding to every reserve command, the headend generates a cycle of length equal to the total number of empty slots reserved. Every cycle is used to serve the reservations made on its corresponding reserve command. Generally, a longer cycle length means a longer access delay and a lower throughput. Therefore, it is desirable to develop a scheme such that the cycle length is the shortest. The authors study the problem of reducing the total number of empty slots generated within every cycle. However, it has been shown that the problem is NP-complete under the constraint that all the empty slots used by a station in a cycle are required to be consecutive. They release the slot-contiguity constraint and propose a fast optimal slot reuse scheme with low time complexity O(M/sup 2/), where M is the number of stations. To evaluate the effectiveness of the slot reuse scheme, a large number of computer simulations are performed. They compare the slot reuse scheme with the original CRMA in terms of the following three important performance measurements: average cycle length, average throughput, and average MAC delay.

One of the most important applications of radio frequency identification (RFID) technology is to detect unknown tags brought by new tagged items, misplacement, or counterfeit tags. While unknown tag identification is able to pinpoint all the unknown tags, probabilistic unknown tag detection is preferred in large-scale RFID systems that need to be frequently checked up, e.g., real-time inventory monitoring. Nevertheless, most of the previous solutions are neither efficient nor reliable. The communication efficiency of former schemes is not well optimized due to the transmission of unhelpful data. Furthermore, they do not consider characteristics of unreliable wireless channels in RFID systems. In this paper, we propose a fast and reliable method for probabilistic unknown tag detection, white paper (WP) protocol. The key novelty of WP is to build a new data structure of composite message that consists of all the informative data from several independent detection synopses; thus it excludes useless data from communication. Furthermore, we employ packet loss differentiation and adaptive channel hopping techniques to combat unreliable backscatter channels. We implement a prototype system using USRP software-defined radio and WISP tags to show the feasibility of this design. We also conduct extensive simulations and comparisons to show that WP outperforms previous methods. Compared with the state-of-the-art protocols, WP achieves more than $2\times$ performance gain in terms of time-efficiency when all the channels are assumed free of errors and the number of tags is 10 000, and achieves up to $12\times$ success probability gain when the burstiness is more than 80%.

Radio Frequency Identification (RFID) anti-collision algorithm is an important technique in RFID field. In this paper, we first mathematically investigate the relationship among the number of tags, the number of slots and the probability of success to read a tag, and then present a precise and reasonable method to evaluate the efficiency of a RFID anti-collision system. In the proposed method, we introduce slot time parameter into the anti-collision process. After introducing the parameter and making it optimal, we find the number of tags no longer equals the number of the frame slots, but fluctuates with the slot time. After the simulation, results show a much better performance.

Passive UHF RFID systems using Dynamic Frame-Slotted ALOHA (DFSA) adjust the frame size according to the number of tags, but frame size N is equals to 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</sup> and cannot be adjusted exactly to the number of tags to be identified. In this paper, we propose an optimal Aloha algorithm (ODFSA), which uses probabilistic approach for tags to access the frame. The Query or Query Adjust packet contains both the parameter Q and P called frame access probability, which represents the ratio of number of active tags in the current frame to the estimated total number of tags which remain to be identified in the system. Estimation of number of unread tags is updated after end of each frame; parameters Q and P are calculated and informed at the beginning of each frame. Mathematical analysis and computer simulations show that the proposed Aloha achieves maximum system efficiency, utilizes less number of slots compared with other algorithms and also takes less identification time.

Radio-frequency identification (RFID) technologies have been widely used in inventory control, object tracking and supply chain management. One of the fundamental system functions is called cardinality estimation, which is to estimate the number of tags in a covered area. In this paper, we extend the research of this function in two directions. First, we perform joint cardinality estimation among tags that appear at different geographical locations and at different times. Moreover, we target at category-level information, which is more significant in practical scenarios where we need to monitor the tagged objects of many different categories. Second, we enforce anonymity in the process of information gathering in order to preserve the privacy of the tagged objects. These capabilities will enable new applications such as tracking how products of different categories are transferred in a large, distributed supply chain. We propose and implement a novel protocol to meet the requirements of anonymous category-level joint estimation over multiple tag sets. We formally analyze the performance of our estimator and determine the optimal system parameters. Moreover, we extend our protocol to unreliable channels and consider two channel error models. Extensive simulations show that the proposed protocol can efficiently and accurately estimate joint information over multiple tag sets at category level, while preserving tags' anonymity.

Slotted ALOHA anti-collision methods have two features. The first feature is that we get the optimal throughput of slotted ALOHA increased if the number of tags and the number of slots are equal. The second feature is that if the number of tags is small and the frame size is equal to the number of tags, the throughput increases as the number of tags decreases. However, most researchers have made little effort to explore the second feature to increase the throughputs of Slotted ALOHA anti- collision methods. In this paper we propose a grouping based dynamic framed slotted ALOHA anti- collision method with fine groups (GB-DFSA) to fully utilize the two features to perform tag identification. We compare the throughput of GB-DFSA with those of the other two methods - EDFSA with partition and DFSA. The results show that the throughput of GB-DFSA is 40% which is higher than EDFSA (38%) with partition and DFSA (31%).

Radio Frequency Identification (RFID) technology has been proliferating in recent years, especially with its wide usage in retail, warehouse and supply chain management. One of its most popular applications is to automatically detect missing products (attached with RFID tags) in a large storage place. However, most existing protocols assume that the IDs of all tags within a reader’s coverage are known, while ignoring practical scenarios where the IDs of some tags may be unknown. The existence of these unknown tags will introduce false positives in those protocols, degrading their performance. Some prior art studies this problem, but their time efficiency is low, especially when the number of unknown tags is large. In this paper, we propose a new missing tag detection protocol based on compressed filters, which not only reduce the filter size for better time-efficiency but also help dampen the interference of unknown tags for high missing-tag detection accuracy. To further improve the performance, we propose to use a combination of sampling and multi-hashing for tags to report their presence, greatly reducing collisions and thus improving the detection probability. We reconfigure the standard ID collection protocol to support bitmap collection required by missing-tag detection. Extensive simulations demonstrate that our compressed filter and collision-reduction method reduce the protocol execution time by 83% to 92% under the same missing-tag detection probability, when comparing with the best prior work. We also evaluate the performance of our missing-tag detection protocol under unreliable channel.