Large-scale Radio Frequency Identification Research Articles

Unknown Tag Identification Protocol Based on Collision Slot Resolution in Large-Scale and Battery-Less RFID System

Radio frequency identification (RFID) technology is widely used in warehouse management and supply chain management. In the actual application, unknown tags such as newly added or incorrectly placed products will be placed into a certain area of the warehouse. Existing identification protocols can identify such unknown tags by collecting tag IDs and comparing them with back-end server. Alternatively, the known tags can be filtered through the filter vector to prevent interference from unknown tags and improve identification efficiency. However, there is a lack of consideration of the collision impact on identification efficiency. In this paper, we introduce the bit tracking technology to accelerate the identification process and propose a Bit-Tracking Based Strategy for Unknown Tag Identification (BTUTI) protocol. We solve the problem by means of known tag deactivation and unknown tag identify. First, by adopting bit tracking technology, the reader can easily locate the positions of the collision bit. By hashing the tags of these collision slots, the collision slots can be turned into resolvable slots, thus improving the utilization rate of slots. Second, in the expected non-empty slot, the reader can send command to deactivate the known tag and skip empty slots and irresolvable collision slots. The experiment proves that BTUTI can increase the time efficiency compared to the state-of-the-art.

Concurrent Rate-Adaptive Reading With Passive RFIDs

Radio frequency identification (RFID)-assisted management systems have been widely applied in warehousing, logistics, retailing, etc. In these scenarios, RFID-aided applications, e.g., object tracking and human behavior sensing, rely on a high-efficiency tag reading to realize accurate analyses and timely responses. However, serious tag collisions in those large-scale RFID systems will inevitably lead to significant decreases in the tag reading rates. To meet the strict timeliness requirements of those practical applications, we aim to treat the individual reading rate for each item tag differently and focus more attention on those user-interactive ones. However, due to unpredictable user behaviors, it is impractical to infer the user-interactive tags in advance. In addition, keeping focusing on them for continuous monitoring despite user movements and multipath-prevalent environments is also challenging. To solve these problems, we propose Spotlight, the first concurrent rate-adaptive reading system in passive RFIDs. Spotlight screens the ID-agnostic user-interactive tags by proposing a multichannel feature for narrow-band RFID systems without any hardware or protocol modification and achieves rate-adaptive reading by implementing real-time MU-MIMO beamforming. Substantial experiments with 1000+ COTS RFID tags exhibit that Spotlight outperforms the commercial reader by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.7\times $ </tex-math></inline-formula> and the SDR-based reader by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6.12\times $ </tex-math></inline-formula> . In addition, Spotlight first proposes the online parallel decoding method to realize concurrency among multiple users, which breaks the commercial protocol’s throughput ceiling (37%) and achieves up to 59% throughputs.

Mayfly Sparrow Search Hybrid Algorithm for RFID Network Planning

The radio frequency identification (RFID) technology is frequently used for large-scale RFID network planning, which brings thought-provoking RFID network planning (RNP) problems such as the uncertain number of readers, high interference rate of readers, poor economic benefits, and weak robustness. In this paper, we propose a mayfly sparrow search hybrid algorithm with Circle chaotic map and Lévy flight, which is named MASSA. MASSA maps out the position of the readers by adding the idea of the mayfly algorithm (MA) into the optimization process of the sparrow search algorithm (SSA). Circle chaos mapping and Lévy flight are added in the SSA optimization process and the nonlinear inertia coefficients to balance the relationship between global search and local search. The MASSA is compared with SSA, Improved sparrow search algorithm (ISSA), MA, particle swarm optimization algorithm (PSO), and gray wolf algorithm (GWO). The first part of the experiment uses the CEC2017 test suite to evaluate algorithm performance and analysis strategy effectiveness. The results encourage the application of MASSA to solve RNP problems. In the second part, experiments were conducted with four objective functions of coverage, interference, power, and load balance. Two different experiments were carried out with fixed number of readers and flexible number of readers under random label conditions. Experimental results show that MASSA has good planning performance, better economy, and robustness.

Efficient and robust missing key tag identification for large-scale RFID systems

Radio Frequency Identification (RFID) technology has been widely used to identify missing items. In many applications, rapidly pinpointing key tags that are attached to favorable or valuable items is critical. To realize this goal, interference from ordinary tags should be avoided, while key tags should be efficiently verified. Despite many previous studies, how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed. Moreover, how to efficiently verify missing key tags in groups rather than one by one has not been explored, especially with varying missing rates. In this paper, we propose an Efficient and Robust missing Key tag Identification (ERKI) protocol that consists of a filtering mechanism and a verification mechanism. Specifically, the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high. Furthermore, the verification mechanism can dynamically verify key tags according to the missing rates, in which an appropriate number of key tags is mapped to a slot and verified at once. Moreover, we theoretically analyze the parameters of the ERKI protocol to minimize its execution time. Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14 ​× ​compared with state-of-the-art solutions.

An Improved Approach for Reader Anti-Collision in Industrial Internet of Things

Radio-frequency identification (RFID) technology has been used in numerous applications, e.g., supply chain management and inventory control. This paper focuses on the practically important problem of reader-to-reader collision in large-scale RFID systems. There are many technical challenges during the existing work such as high computational complexity and low identification efficiency. To tackle the above challenges, this paper proposes a novel reader anti-collision protocol optimized by minimal reverse weight (NRA-MRW), which includes two phases. Extensive simulation results show that our proposed NRA-MRW can improve the identification efficiency and system throughput over the existing protocols by 25.2% and 12.3%, respectively.

A More Accurate and Stable Batch Authentication Protocol for Large-Scale RFID Systems

In this letter, a batch authentication protocol called as accurate bloom-filter-based batch authentication (ABBA) protocol is presented for large-scale radio-frequency identification (RFID) systems. Similar to its predecessor BBA, ABBA can estimate the number of invalid tags contained in an unknown tag set in one communication round by exploiting a bloom filter (BF) vector constructed distributively by the tags. Whereas different from BBA, ABBA adopts a novel BF vector construction method where the randomness caused by valid tags is removed, and thus the estimation is guaranteed to be more accurate and stable than BBA. Both theoretical analysis and extensive simulations confirm the superiority of ABBA over BBA.

Efficient and accurate identification of missing tags for large-scale dynamic RFID systems

The future real-world applications is bound up with Radio frequency identification (RFID) technology as it develops dramatically fast, especially in the field of warehouse management and inventory control, etc. In such applications, identifying missing tags to determine which goods are missing is an important issue. However, since only static scenarios with no new tag movement are considered, existing missing tag identification protocols hardly work well in more common dynamic scenarios where there are tags entering the system or missing frequently. In highly dynamic RFID systems, identifying missing tags becomes more challenge under the interference of unknown tags. Existing methods suppress this interference by filtering unknown tags, which is time-consuming and inefficient. In this paper, for high dynamic RFID systems, we propose an efficiently and accurately protocol HDMI to identify missing tags. By combining the reply slot location of the tags and the reply bits, HDMI identifies missing tags and filters the unknown tags simultaneously, which maximizes the slot utilization. We also optimize the setting of key parameters to reduce execution time while ensuring recognition accuracy. Simulation results show that, compared with state-of-art protocols, HDMI has a higher accuracy rate and better time efficiency in identifying missing tags.

A Priority-Based Tag Identification Protocol for the Large-Scale RFID System

Radio Frequency Identification (RFID) technology has been widely deployed in IoT-enabled applications because of its cheapness, simultaneous multi-item-identification, and strong information storage capability. In a large-scale RFID system, all tags belong to different groups according to the item-associated brand, value, or danger class. However, the existing works assume that groups equally share the maximum identification efficiency 36.8% under the optimal parameter settings. This letter proposes a Priority-based Tag Identification (PTI) protocol for RFID systems. In PTI, the high priority group enjoys a higher identification efficiency than the low priority groups. This is achieved by using the priority queue technique, which enables the reader to detect the tags with the highest priority and only allows them to respond to the reader. Our experiments show that due to the benefit of priority queues, the maximum slot efficiency of the PTI protocol can be improved to 78.9%.

Reader Scheduling for Tag Population Estimation in Multicategory and Multireader RFID Systems

Radio Frequency Identification (RFID) technology has been used in numerous applications, e.g., supply chain management and inventory control. This paper focuses on the practically important problem of the rapid estimation of the number of tags in large‐scale RFID systems with multiple readers and multicategory RFID tags. RFID readers are often static and have to be deployed strategically after careful planning to cover the entire monitoring area, but reader‐to‐reader collision (R2Rc) remains a problem. R2Rc decreases the reliability of the estimation of the tag population size, because it results in the failure of communication between the reader and tags. In this paper, we propose a coloring graph‐based estimation scheme (CGE), which is the first estimation framework designed for multireader and multicategory RFID systems to determine the distribution of tags in different categories. CGE allows for the use of any estimation protocol to determine the number of tags, prevents R2Rc, and results in higher time efficiency and less power‐consumption than the classic scheduling method DCS.

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

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.

Nowhere to Hide: Efficiently Identifying Probabilistic Cloning Attacks in Large-Scale RFID Systems

Radio-Frequency Identification (RFID) is an emerging technology which has been widely applied in various scenarios, such as tracking, object monitoring, and social networks, etc. Cloning attacks can severely disturb the RFID systems, such as missed detection for the missing tags. Although there are some techniques with physical architecture design or complicated encryption and cryptography proposed to prevent the tags from being cloned, it is difficult to definitely avoid the cloning attack. Therefore, cloning attack detection and identification are critical for the RFID systems. Prior works rely on that each clone tag will reply to the reader when its corresponding genuine tag is queried. In this article, we consider a more general attack model, in which each clone tag replies to the reader's query with a predefined probability, i.e., attack probability. We concentrate on identifying the tags being attacked with the probability no less than a threshold $P_{t}$ with the required identification reliability $\alpha $ . We first propose a basic protocol to Identify the Probabilistic Cloning Attacks with required identification reliability for the large-scale RFID systems called IPCA. Then we propose two enhanced protocols called MS-IPCA and S-IPCA respectively to improve the identification efficiency. We theoretically analyze the parameters of the proposed IPCA, MS-IPCA and S-IPCA protocols to maximize the identification efficiency. Finally we conduct extensive simulations to validate the effectiveness of the proposed protocols.

A vehicle routing model based on large-scale radio frequency identification data

The rapid development of sensing, computing, and wireless communication techniques has given rise to an increasing number and increasing availability of high-resolution data that record real-time traffic information. In this study, radio frequency identification (RFID) data collected in Nanjing (a major city in southern China) were used to estimate dynamic travel demands and develop an RFID data-based vehicle routing model that simultaneously considers individual benefits and social good. The proposed vehicle routing model also used information regarding driver origins that contribute to major congestion; therefore, the routing model can be applied to a group of targeted vehicles only, providing more adaptive, efficient, and feasible routing strategies to mitigate traffic congestion.

Redundant Reader Elimination in Large-Scale Distributed RFID Networks

Radio frequency identification (RFID) is a key enabling technology for large-scale Internet of Things (IoT). Its deployment and management impact significantly on the operational effectiveness and scalability of IoT. Redundant reader elimination is of great importance to reduce the system’s overhead and prolong the lifetime of RFID networks. It helps to reduce unnecessary reader-tag interactions and the cost of collision avoidance algorithm in distributed data collection of RFID network. In large-scale distributed RFID networks, one of the most challenging tasks for redundant reader elimination is to improve the performance of distributed algorithms. This paper proposes a novel distributed redundant reader elimination algorithm based on the threshold selection process, named threshold selection algorithm (TSA), for RFID networks. TSA algorithm selects effective reader iteratively based on the threshold sequence determined by expected tag coverage. This paper also introduces an optimization mechanism into TSA based on detected movement, named TSA with movement detection algorithm. By preliminary simulation, we determine the suggested parameter of linear multiplier for TSA. Our experiments show that TSA algorithm can provide 30%–60% better performance than other major distributed algorithms and also multiphase schemes in both dense and sparse environments. The overhead of TSA algorithm is 30%–50% lower than other selected algorithms, especially in tag-write operations.

A Highly Efficient Predetection-Based Anticollision Mechanism for Radio-Frequency Identification

One of the research areas in radio-frequency identification (RFID) systems is the reduction of the identification processing time for a number of tags within an RFID reader recognition region. In the last decade, many research results regarding anticollision algorithms have been presented in the literature. Most of them are tree-based protocols. However, it is important for tree-based protocols to enhance stability and system throughput, since they may face long identification delays when the network density is high. In this study, we present a highly efficient predetection tree-based algorithm to achieve more efficient tag identification performance. Our proposed mechanism can effectively reduce both collisions and idle cycles by exploiting the predetection technique and adjustable slot size mechanism. The simulation results show that the proposed mechanism can effectively improve tag identification time performance by around 29.9% to 64.8% over previous techniques. Further, the number of query cycles, number of collisions, and total number of slots are reduced compared to previous predetection-based protocols. It is also observed that the proposed scheme can have good performance in large-scale RFID systems.

A Time-Efficient Pair-Wise Collision-Resolving Protocol for Missing Tag Identification

Radio frequency identification (RFID) technology has been employed in wide-raging application domains. In most RFID applications, time-efficient identification of missing tags is one of the most fundamental objectives, especially for asset management and anti-theft purposes. In this paper, we propose a time-efficient pair-wise collision-resolving missing tag identification (PCMTI) protocol for large-scale RFID systems. In the protocol, two novel strategies, i.e., the pair-reply and two-collision slot (i.e., a slot with two exact tag responses) resolving strategies, are proposed. The pair-reply strategy can verify two tags in one short response slot simultaneously, while the two-collision slot resolving strategy further increases the number of tags verified in each frame. Both theoretical analysis and simulated results are presented to demonstrate the superiority of the proposed PCMTI protocol, which is capable of outperforming the state-of-the-art comparative protocols with at least a 30% reduction in average identification time for verifying one tag.

Fast and secure tag authentication in large-scale RFID systems using skip graphs

Fast and secure object monitoring and management using Radio Frequency Identification (RFID) technologies is crucial to Internet of Things (IoT) systems. Structured key-based private authentication protocols securely identify individual RF tags in the logarithmic order by having group keys shared by several tags. However, should some portion of tags in the system be physically compromised, the degree of privacy of the other tags will decrease. This is because tampered group keys disclosed from the compromised tags can be correlated. Thus, preserving the degree of tags’ privacy in keeping with fast authentication speed is equivalent to reducing the correlation probability of group keys. Toward this goal, we propose Randomized Skip Graphs-Based Authentication (RSGA) that significantly improves the tags’ privacy in terms of anonymity with reasonable amount of key storage cost by using a skip graph key structure. Then, we augment RSGA with a key updating mechanism to securely update secret keys and a path pruning algorithm to further facilitate its authentication process. Our extensive computer simulation as well as mathematical analyses present that the proposed RSGA achieves its design goals.

Efficient Unknown Tag Detection in Large-Scale RFID Systems With Unreliable Channels

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%.

Efficient and Reliable Missing Tag Identification for Large-Scale RFID Systems With Unknown Tags

Radio frequency identification (RFID), which promotes the rapid development of Internet of Things (IoT), has been an emerging technology and widely deployed in various applications such as warehouse management, supply chain management, and social networks. In such applications, objects can be efficiently managed by attaching them with low-cost RFID tags and carefully monitoring them. The missing objects, therefore, can be identified by the readers in the RFID system. Most of prior missing tag identification protocols consider the ideal scenario that all the tags’ IDs are known to the reader, which ignore that some tags with unknown IDs, called unknown tags, may be present in the system. In this paper, we investigate the problem of efficiently identifying the missing tags with a predefined reliability for large-scale RFID systems with unknown tags. We first propose a basic efficient and reliable missing tag identification protocol called B-ERMI. Then we propose an enhanced protocol called E-ERMI to further improve the efficiency. The parameters of our proposed ERMI protocols are optimized to minimize the execution time. We also conduct extensive simulations to evaluate the proposed ERMI protocols and the simulation results illustrate that the ERMI protocols outperform other existing ones.

Toward More Rigorous and Practical Cardinality Estimation for Large-Scale RFID Systems

Cardinality estimation is one of the fundamental problems in large-scale radio frequency identification systems. While many efforts have been made to achieve faster approximate counting, the accuracy of estimates itself has not received enough attention. Specifically, most state-of-the-art schemes share a two-phase paradigm implicitly or explicitly, which needs a rough estimate first and then refines it to a final estimate meeting the desired accuracy; we observe that the final estimate can largely deviate from the expectation due to the skewed rough estimate, i.e., the accuracy of final estimates is not rigorously bounded. This negative impact is hidden because former solutions either assume perfect rough estimates or rough estimates that can be produced by uniform random data or perfect hash functions that can turn any data into uniform random data. Unfortunately, both of them are hard to meet in practice. To address the above issues, we propose a novel scheme, namely, “rigorous and practical cardinality (RPC)” estimation. RPC adopts the two-phase paradigm, in which the rough estimate is derived in the first phase using pairwise-independent hashing. In the second phase, we employ $t$ -wise-independent hashing to reinforce the rough estimate to meet arbitrary accuracy requirements. We validate the effectiveness and performance of RPC through theoretical analysis and extensive simulations. The results show that the RPC can meet the desired accuracy all the time with diverse practical settings while previous designs fail with non-uniform data.

Cardinality estimation using collective interference for large-scale RFID systems

Estimating the number (cardinality) of Radio Frequency Identification (RFID) tags is a principal problem for large-scale RFID systems. This paper proposes a novel protocol for RFID cardinality estimation using synchronized response signals. For every estimation round, we need a single time-slot to parse multi-bit information from the synchronized signals that are concurrently transmitted from tags. Our protocol guarantees satisfaction of an arbitrary accuracy requirement within the smallest number of time-slots compared to existing estimation protocols. The efficiency of our protocol is based on two components: tags' synchronization and random number generation from a geometric distribution. We design these components to be feasible without heavy computation or memory overhead, and our protocol can be applied to low-cost and resource-constrained passive RFID tags. We have implemented a proof of concept prototype using software defined radio and programmable RFID tags. By conducting large-scale simulations, we have shown that our protocol outperforms the existing cardinality estimation protocols.