Efficient Tag Identification Research Articles

A Method to Enhance Tag Identification Efficiency Based on Tail Code Optimization Feature Sets

A Method to Enhance Tag Identification Efficiency Based on Tail Code Optimization Feature Sets

MPSK Orthogonal Coset Identification for Massive RFID Network

Efficient tag identification is critically important for the application of radio frequency identification (RFID). The recently proposed orthogonal coset identification (OCSID) achieves orthogonal tag ID scanning without spectrum spreading so that the tag IDs can be recovered from collision. In the OCSID, the IDs are generated from binary vector set $\{-1, +1\}^{B}$ , which is only available for binary modulation. In this letter, we show that $B$ dimensional $M$ order vector set $\left\{{1, e^{\mathrm {i}\frac {2\pi }{M}}, {\dots }, e^{\mathrm {i}\frac {2\pi (M-1)}{M}}}\right\}^{B}$ can be decomposed to $\frac {M^{B}}{B}$ disjoint orthogonal subsets, where $M$ is the modulation order, $B$ is a positive integer power of 2. Based on this, we generalize the OCSID from binary to arbitrary order and propose $M$ -ary phase shift keying (MPSK) OCSID. We show a possible way to adopt the MPSK OCSID into EPC global C1 Gen2 standard, and with the consideration of the synchronization error, we also present a hybrid of the MPSK OCSID and the Aloha. Numerical results show that the MPSK OCSID based protocol can considerably improve the efficiency, even for the non-perfect synchronization cases.

Hybrid Predetection Technique for Efficient Tag Identification in Radio-frequency Identification Systems

Hybrid Predetection Technique for Efficient Tag Identification in Radio-frequency Identification Systems

An Efficient Tag Identification Algorithm Based on Improved Collision Detection

An Efficient Tag Identification Algorithm Based on Improved Collision Detection

Toward Efficient Compressed-Sensing-Based RFID Identification: A Sparsity-Controlled Approach

Radio-frequency identification (RFID) has pervasive applications in building ultralow-power ubiquitous networks, where backscatter communication during tag identification is neither reliable nor efficient. Inspired by the sparsity that only a few RFID tags communicate with the reader simultaneously, many compressed sensing (CS)-based schemes have been proposed to exploit the colliding tag responses to facilitate efficient tag identification. However, most of them suffer from huge ID search space and signature collision during the CS recovery process. To address these issues, we propose SCRIC, a novel sparsity-controlled RFID identification scheme using a random signature assignment, which achieves a faster and more robust identification performance. Specifically, to tackle identification failure caused by severe signature collision, we assign each active tag an access probability to control the sparsity and reduce signature collision. Theoretical analysis is given to prove that the signature collision probability of the proposed scheme is reduced compared with the existing random signature scheme and an optimal access probability is derived. Moreover, considering that conventional CS recovery algorithm relies heavily on the unpractical assumption that the active tag number is known precisely in advance, we integrate the cross validation (CV) into CS recovery algorithms and propose a greedy algorithm called the CV-based orthogonal matching pursuit (OMP-CV), which can reduce the tag identification false alarm rate without any prior knowledge. Extensive experimental results show that the proposed mechanism significantly outperforms the existing CS-based tag identification methods in terms of identification speed and robustness to noise.

Smart Batch-Processing Protocol for RFID Multiple Tag Identification

The common paradigm of the RFID network is to obtain data from multiple tags through a reader. The tag collision problem seriously affects the efficiency of tag identification. The anti-collision algorithm provides a reliable guarantee to identify multiple tags as fast as possible. Many papers have proposed query tree algorithms based on bit tracking, but these algorithms still have problems such as idle paging and redundant prefixes. In this paper, we start with an analysis of state-of-the-art anti-collision algorithms. Based on summarizing current works, we propose a Smart Batch-Processing protocol (SBP) for RFID multiple tag identification based on M-ary collision bit arbitration mechanism. In the SBP, the reader firstly maps m-bit collision bits into 2 m slots and then predicts the distribution of tags in slots. Finally, the reader allows the tag to return the remaining part of its ID at the mapped slot using a batch-processing command. By using SBP, the reader can simultaneously identify 2 m groups of tags in a slot. Besides, empty queries can be eliminated in the tag identification process. The description of SBP is given first, and then, its performance is theoretical analyzed and simulated. Both theoretical analysis and extensive simulation results show that the SBP algorithm reduces 22.94% and 22.28% of time and energy consumption compared to other M-ary collision bit arbitration based methods.

TMIA: A Tree-Based Multi-Reader Interactive Anti-Collision Algorithm for RFID Tag Identification

In the RFID system, the tag collision problem seriously affects the efficiency of tag identification. Among the anti-collision algorithms, tree-based anti-collision algorithms are popular for the reason that they can ensure that the tags can theoretically 100% be identified by readers. As multi-reader scenarios are more and more widely used in complex internet of things environments, there are more collision slots and idle slots in traditional anti-collision algorithms, which affects the efficiency of the algorithm. We propose a tree-based multi-reader interactive anti-collision algorithm (TMIA) for multi-reader tag identification scenarios to solve the problems above. Readers optimize the broadcast prefix sequence by sharing the broadcast results. The proposed algorithm works in two phases: In the first phase, the reader selects a suitable broadcast prefix by the multi-reader inverse probability function (MIPF) to reduce the initial redundant collision in tag identification. In the second phase, the priority of the broadcast prefix is adjusted through the information exchange between readers, the readers thus avoid broadcasting a large number of invalid prefixes. Theoretical analysis and simulation results show that TMIA has a lower total number of slots and better system efficiency than existing tree-based algorithms. TMIA also greatly reduce the number of collision slots.

Privacy of Stateful RFID Systems With Constant Tag Identifiers

There is a major interest in designing RFID schemes based on symmetric-key cryptography and ensuring efficient tag identification. These requirements taken together often lead to a decrease in the degree of privacy provided by the scheme. This issue, as we know, has been treated in an ad-hoc manner so far. In this paper, we introduce the class of stateful RFID schemes with constant tag identifiers , that ensure tag identification in no more than logarithmic time. In order to study their privacy, we propose an appropriate general model obtained by constraining Vaudenay’s model. We then propose two symmetric-key cryptography based RFID schemes in this class that achieve weak and destructive privacy, respectively, in addition to mutual authentication. We also discuss on the degree of privacy provided by other schemes proposed in the literature, that fall in this class.

An Efficient Tag Identification Scheme based on the Reader’s Power Control

This paper proposes an efficient tag identification scheme for ISO/IEC18000-7 standard by dividing the tags into smaller groups. Tag grouping is based on the reader’s transmission power. This can reduce the responding tags in the collection round. If the small number of tags exists, we can anticipate the collision probability will decrease. And it makes the identification speed high. A collection round initiated by the reader’s collection command. It also proceeds with increasing the power of the reader until all tags are identified. The results showed that 25% of the performance improved.

An Optimized NS2 Module for UHF Passive RFID Systems

Radio Frequency Identification (RFID) technology has the potential to dramatically improve numerous industrial practices. However, it still faces many challenges, including tag collisions and reliability, which may limit its use in many application scenarios. In UHF RFID systems, many collisions happen due to the numerous tag responses generated by the inventory process. Also, given the low cost and low performance of UHF RFID tags combined with harsh environments, RFID communications must deal with high Bit-Error-Rate (BER). As a matter of fact, the extra identification delays added by these collisions and communication errors can bring to a waste of bandwidth and more time inventory. The efficiency of tag identification is related to the performance of the anti-collision algorithm. To evaluate this performance, an UHF RFID module has already been developed in the NS2 simulator. This NS2 RFID module implements an RFID system based on the anti-collision Q-Algorithm (Q-Algo) of the EPC Global Protocol Class-1 Generation-2 Standard. In this paper, first, we propose an optimization of this NS2 RFID module by implementing and validating a more realistic version of the Q-Algo. Secondly, we add to this module some fault injection capabilities to evaluate with NS2 the UHF RFID system robustness in presence of communication errors. Finally, we show how this NS2 UHF RFID module is much more realistic for the timing evaluation in presence of communication errors.

A Collision Resolution Algorithm for RFID Using Modified Dynamic Tree With Bayesian Tag Estimation

A new tree-based anti-collision protocol for radio-frequency identification systems is proposed to achieve a very high tag identification efficiency. The proposed algorithm works in two phases. In the first phase, the number of competing tags is estimated through the proposed Bayesian estimation technique, while in the second phase, tags are identified using our modified dynamic tree algorithm. The system efficiency is mathematically derived and verified through simulation. Numerical results show that the proposed algorithm achieves a tag identification system efficiency of 45% and a time system efficiency of 78.5%, thus outperforming any existing collision resolution algorithms.

A Time- and Energy-Aware Collision Tree Protocol for Efficient Large-Scale RFID Tag Identification

Being able to provide a relatively easy and inexpensive way to collect data, portable readers have gained increasing popularity in wide-ranging RFID applications. In order to maximize the reader’s battery life, efficient tag identification protocols are of paramount importance in large-scale passive radio frequency identification (RFID) systems. This paper proposes a time- and energy-aware protocol based on $M$ -ary collision tree (MCT) for efficient RFID tag identification. Thanks to Manchester encoding, the proposed MCT protocol recursively divides colliding tags into $M$ subsets with at least two nonempty ones according to the information of $\log _2 M$ colliding bits. Through the new MCT recognition process, MCT can effectively identify all the tags within its reading range. Theoretic analysis demonstrates that it takes the proposed MCT protocol fewer numbers of collision slots and message bits to identify all the tags, which reduces not only the identification time but also the energy cost. Simulation results are also presented to show that compared with other benchmark works, the proposed MCT protocol is able to reduce the average identification time and energy cost by at least 16.12% and 15.73%, respectively.

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.

An Efficient and Easy-to-Implement Tag Identification Algorithm for UHF RFID Systems

In this letter, a novel sub-frame-based dynamic frame slotted ALOHA (DFSA) algorithm is proposed for efficient tag identification based on EPC C1 Gen2 radio frequency identification (RFID) standard. Through the observation of slot states in a sub-frame, the reader estimates the tag number, and quickly adjusts the frame length to match the quantity of backlog. Once the appropriate frame length is observed, the algorithm will return to traditional DSFA. We use the modified maximum a posteriori probability (MAP) method for the estimation of tag quantity to improve the accuracy. To reduce the computation complexity of traditional MAP, we use tables to store estimation numbers. Due to the length strict of sub-frames, only a relatively small size of memory is required. Simulation results show that dynamic sub-frame MAP can improve the system utility (approximately 0.36) and reduce the computation complexity, only with an addition of less than 3-kB memory.

A Two-way Hybrid Query Tree Anti-collision Algorithm

Based on the Hybrid Query tree algorithm, this new algorithm compares the sums of collision distances: in forward direction, utilizing the combined information of the highest and the second highest bit of collision, categorizes the tags and decides gaps of delay to reduce collision; In reverse, utilizing collision template to form identification tree by using leaf nodes of electronic tags. The findings from the simulated experiments show that this proposed algorithm is superior to QT and HQT by decreasing the number of query and the traffic volume of system communication so that the efficiency of tag identification is greatly enhanced.

Design of a Quaternary Query Tree ALOHA Protocol Based on Optimal Tag Estimation Method

Radio Frequency Identification (RFID) technology is one of the most promising technologies in the IoT (The Internet of Things) era. Many RFID systems have been used in supermarkets or warehouses. There are two challenges for RFID anti-collision algorithms. The first challenge is accurately estimating the number of tags; the other is improving the efficiency of RFID systems. This paper proposes an optimal tag estimation method in which tags respond to the reader in assigned time slots instead of responding randomly. In order to improve the performance of the RFID system, a 4-ary query tree Additive Link On-line HAwaii (ALOHA) protocol is presented that combines the merits of query tree algorithm and frame slotted ALOHA, and avoids their weaknesses. Simulation results show that the proposed algorithm has a higher tag identification efficiency compared to other dynamic frame slotted ALOHA algorithms, and it can overcome the tag starvation phenomenon, because it traces each tag until all of them are identified successfully.

Flexible and Time-Efficient Tag Scanning with Handheld Readers

Tag scanning is an important issue to dynamically manage tag IDs in radio frequency identification (RFID) systems. Different from tag identification that collects IDs of all the tags, tag scanning first verifies whether or not a responding tag has already been identified and retrieves its ID when the answer is yes, and collects the tag's ID only when it is unidentified. In this paper, we present the first study on spot scanning with a handheld reader, which aims to scan tags in the reader's interrogation range at an arbitrarily specified position in the system. Existing studies mainly focus on continuous scanning , and they are highly time inefficient in performing spot scanning. The inefficiency stems from the small overlap between tag populations in different spot scanning operations, in which case existing solutions cannot efficiently recognize unidentified tags. We develop a novel technique called LOCK to efficiently recognize unidentified tags even when the overlapped tags are few. LOCK does not simply use a tag's reply slot index but also compact short responses from tags to efficiently distinguish unidentified tags from identified ones. The valuable compact short responses are firstly investigated, which are the keys for efficient tag identification in the paper. Based on LOCK, three tag scanning protocols are proposed to solve the spot scanning problem. Simulation results show that, for spot scanning, our best protocol reduces per tag scanning time by up to 70 percent when compared with the state-of-the-art solution. Moreover, the proposed protocols can also be employed to perform continuous scanning with better time efficiency than the best existing solutions.

An Effective Scheduling-Based RFID Reader Collision Avoidance Model and Its Resource Allocation via Artificial Immune Network

Radio frequency identification, that is, RFID, is one of important technologies in Internet of Things. Reader collision does impair the tag identification efficiency of an RFID system. Many developed methods, for example, the scheduling-based series, that are used to avoid RFID reader collision, have been developed. For scheduling-based methods, communication resources, that is, time slots, channels, and power, are optimally assigned to readers. In this case, reader collision avoidance is equivalent to an optimization problem related to resource allocation. However, the existing methods neglect the overlap between the interrogation regions of readers, which reduces the tag identification rate (TIR). To resolve this shortage, this paper attempts to build a reader-to-reader collision avoidance model considering the interrogation region overlaps (R2RCAM-IRO). In addition, an artificial immune network for resource allocation (RA-IRO-aiNet) is designed to optimize the proposed model. For comparison, some comparative numerical simulations are arranged. The simulation results show that the proposed R2RCAM-IRO is an effective model where TIR is improved significantly. And especially in the application of reader-to-reader collision avoidance, the proposed RA-IRO-aiNet outperforms GA, opt-aiNet, and PSO in the total coverage area of readers.

Passive RFID Tag Anticollision Algorithm for Capture Effect

Capture effect is very common in passive radio frequency identification systems. Even though multiple tags transmit their signals to a reader simultaneously, one of the tags will be successfully identified due to capture effect. However, capture effect may hide some tags. Many existing algorithms that assume no capture effect will miss the hidden tags. In this paper, we extend an existing algorithm to the capture effect environment and propose a novel tag anti-collision algorithm to enhance the efficiency of tag identification. The proposed algorithm adopts an allocation strategy to reduce collision between the hidden tags by capture effect and the other tags. The strategy lets the collided tags resolved in a current cycle immediately. On the other hand, the hidden tags will enter the next cycle. Thus, the resolved tags will not collide with the hidden tags in the next cycle, and the collision will be reduced. The experiment results show that the proposed protocol's identification efficiency outperforms other existing protocols when the occurrence probability of capture effect varies from 0.1 to 0.6.

A Novel RFID Tag Identification Protocol: Adaptive $$n$$ n -Resolution and $$k$$ k -Collision Arbitration

Since radio frequency identification (RFID) technology has become increasingly common in numerous applications, including large-scale supply chain management, improving the efficiency of RFID tag identification is an important task. In practical settings, the identification of RFID tags often occurs in a dynamic environment, in which tags move through a specific interrogation range. However, the literature contains few studies on the design of efficient identification protocols in dynamic environments. This study proposes a novel tag identification protocol that is particularly efficient in dynamic environments. the proposed protocol involves two anti-collision techniques: adaptive n-Resolution (AnR) and k-Collision Arbitration (kCA). These two techniques significantly improve the tag identification delay and communication overhead. This improvement is primarily due to the use of a newly designed challenge-response bit sequence mechanism and the information obtained from the previous tag identification procedure. As a result, AnR requires only a constant number of interrogation times regardless of the number of target tags, while kCA further improves the efficiency of tag identification with $$k$$ k -splitting collision arbitration. Rigorous analysis and simulation experiments show that this tag identification protocol significantly outperforms related methods (by at least 48.85 % identification delay and 23.87 % communication overhead can).