Dynamic Framed Slotted ALOHA Research Articles

An Effective Tag Estimation Method Based upon Artificial Neural Networks and Signal Strength for Anticollision in Radio Frequency Identification Systems

Radio frequency identification (RFID) technology has been widely used in applications such as access control, inventory management, spatial positioning, and object identification. Accurate tag estimation is one of the major challenges in RFID reader systems particularly in areas where large tag populations are to be identified such as shopping carts, warehouse inventory monitoring, and small ruminant farms. This paper proposes a new tag estimation technique employing artificial neural networks (ANNs) and signal strength to read large tag populations. The technique estimates the number of tags through the signal strength of the backscatter channel for efficient implementation of dynamic framed slotted Aloha (DFSA) protocol by analyzing the RN16 and the received signal strength indicator (RSSI). The ANN model is trained using the signal strength of various tag populations and can identify the number of tags with minimal errors. The proposed technique does not require any modification in the tags and is implemented as a minimal software script to be added to the tag estimation module of the reader. The proposed signal strength-ANN model is able to estimate the accurate number of tags thereby improving the performance of the employed DFSA model.

Improved tag estimation method for TDMA anticollision protocols using CA-CFAR technique

Abstract Radio Frequency Identification (RFID) is considered a key element of the Internet of Things (IoT). It enables objects to be identified and tracked using radio waves. In RFID systems, several tags may be present within the range of the reader, leading to collisions and interference between signals that reduce system performance. Several anti-collision solutions have been proposed to solve this problem based on TDMA (Time-Division Multiple Access) technique, such as the ALOHA, Slotted ALOHA and Dynamic Framed Slotted ALOHA (DFSA) protocols. In this paper, we propose to improve TDMA anti-collision protocols based on the Cell Averaging Constant False Alarm Rate (CA-CFAR) scheme. The CA-CFAR technique is introduced to estimate the number of tags in the physical layer so that the reader can adjust its transmission parameters accordingly and avoid collisions. The obtained results show that this technique achieves good results in terms of system efficiency and the number of required slots to identify all the tags of the system.

Efficient Tag Grouping RFID Anti-Collision Algorithm for Internet of Things Applications Based on Improved K-Means Clustering

Dynamic Frame Slotted ALOHA (DFSA) is a de facto algorithm in the EPC Global Class-1 Generation-2 protocol for Radio Frequency Identification (RFID) tag collision problem. DFSA fails when the UHF RFID tag deployment becomes dense like in Internet of Things (IoT). Existing works do not provide readers prior tag estimates. Most algorithms assume a collision slot means two tag collision. But in dense IoT applications, much more than two tags can constitute a collision slot. Moreover, research proves collision slot might occur due to other reasons such as error-prone channel. This paper proposes a RFID anti-collision algorithm, kg-DFSA that equips the reader with prior information on accurate tag estimate. In kg-DFSA, tag identification is divided into two stages – initialization and identification. In the initialization stage, the reader uses improved K-means clustering running concurrently with a tag counter algorithm to cluster tags into K groups using tags’ RN16 while the counter returns an accurate tag number estimate. In the identification stage, the tags are read only in frame chunks that match their group IDs while a new frame size look up table is developed to boost efficiency. Variants of the proposed kg-DFSA, traditional DFSA and another grouping based DFSA algorithm (FCM-DFSA) were implemented in MATLAB. Extensive Monte Carlo simulation shows the proposed kg-DFSA edges DFSA in terms of success rate 50%, system efficiency 65% and identification time 28%. The proposed model is useful in enhancing the existing MAC protocol to support dense IoT deployment of RFID.

Grouping based radio frequency identification anti-collision protocols for dense internet of things application

<span lang="EN-US">Radio frequency identification (RFID) is an important internet of things (IoT) enabling technology. In RFIDs collision occur among tags because tags share communication channel. This is called tag collision problem. The problem becomes catastrophic when dense population of tags are deployed like in IoT. Hence, the need to enhance existing dynamic frame slotted ALOHA (DFSA) based electronic product code (EPC) C1G2 media access control (MAC) protocol. Firstly, this paper validates through simulation the DFSA theory that efficiency of the RFID system is maximum when the number tags is approximately equal to the frame size. Furthermore, literature review shows tag grouping is becoming popular to improving the efficiency of the RFID system. This paper analyzes selected grouping-based algorithms. Their underlining principles are discussed including their tag estimation methods. The algorithms were implemented in MATLAB while extensive Monte Carlo simulation was performed to evaluate their strengths and weaknesses. Results show that with higher tag density, fuzzy C-means based algorithm (FCMBG) outperformed traditional DFSA by over 40% in terms of throughput rate. The results also demonstrate FCMBG bettered other grouping-based algorithms (GB-DFSA and GBSA) whose tag estimation method are based on collision slots in terms slot efficiency by over 10% and also in terms of identification time.</span>

A Novel Computation Method for Tag Estimates in DFSA-based RFID Systems

In this paper, we propose a novel computation method for tag estimation in the dynamic framed slotted ALOHA (DFSA) protocol, based on Vogt’s estimate (VE). The estimation target is system load λ and tag estimate N̂ is computed from the estimated values of λ, instead of the direct approach taken in the existing method. Starting from the definition of VE, we derive a single concise equation for the estimate. For the numerical solution, we present a load estimation algorithm, which turns out to be computationally very efficient. The computational complexity is roughly O(10 log<SUB>10</SUB> N<SUB>max</SUB>), in contrast to O(N<SUB>max</SUB>) in the existing method for maximum possible number of tags, N<SUB>max</SUB>. Through computer simulations, we show that the proposed method indeed yields estimation results almost identical to those by the existing method in most cases.

Scalable Wi-Fi Backscatter Uplink Multiple Access for Battery-Free Internet of Things

This paper presents a scalable uplink multiple access (SUMA) protocol for bistatic Wi-Fi backscatter systems, composed of a Wi-Fi reader, Wi-Fi helper, and multiple Wi-Fi backscatter tags. SUMA uses a Wi-Fi reader-initiated dynamic framed slotted ALOHA (DFSA)-based multiple access protocol to minimize collisions caused by simultaneous Wi-Fi backscatter uplink traffic from multiple Wi-Fi backscatter tags. In SUMA, the Wi-Fi helper first estimates the number of tags at the start of network operation and derives an appropriate slot-count parameter (i.e., Q), based on which the frame size is specified. Then, the Wi-Fi helper adaptively adjusts the value of Q to maximize network performance while continuously monitoring the number of remaining Wi-Fi backscatter tags to detect information. An experimental simulation was performed to verify the superiority of SUMA. The results demonstrated that SUMA obtained higher performance in terms of the number of collided and empty slots, delay, and throughput compared with the legacy DFSA approach adopted in the EPCglobal Class 1 Gen 2 standard.

A Novel Frame-Slotted ALOHA Algorithm for Radio Frequency Identification System in Supply Chain Management

Abstract Radio Frequency Identification (RFID) is an essential wireless technology with different supply chain management (SCM) potential applications. Managing a supply chain primarily requires an ‘information sharing’ architecture and visibility of business process-related data. This information architecture helps the operational event management team identify critical incidents and deploy substitute actions. The RFID-based information system provides a technological infrastructure to supply chain business process-related data. The occurrence of tag-collision incident essentially challenges the tag detection ability of RFID systems. Tag collision takes place when more than one tag responds simultaneously to the reader at the identification process. Different algorithmic solutions are available to the tag collision problem. In general, the algorithmic solutions are of two types: (i) tree-based solutions, and (ii) ALOHA-based solutions. This paper presents a novel dynamic frame slotted ALOHA algorithm. It uses probability theory for tags to access the frame and improve the system efficiency. This paper presents experimental details to evaluate the performance of the Electronic Product Code Generation-2 (EPC Gen-2) arbitration algorithm. Finally, the paper discusses the experimental results of the proposed algorithm, and concludes with the scope of future research.

RFID Technology Based on Internet of Things in Public Library

The goal of this article is to study the application of Internet of Things RFID technology in public libraries, and to find better algorithms to improve the efficiency of RFID technology in public libraries. The method is to find the problems that affect the efficiency of the RFID system according to the actual needs of the system in the public library, and try to optimize and improve the algorithm. This article first uses the principle of RFID technology as an entry point and introduces the principle of pure ALOHA algorithm in detail. Given its throughput rate curve with the amount of communication tags, this paper introduces the improved frame slot ALOHA algorithm based on the slot ALOHA algorithm. Then it introduces the tag quantity estimation mechanism, tag polling mechanism and privacy protection mechanism, analyzes several commonly used RFID tag quantity estimation mechanisms, and discusses the three RFID privacy protection mechanisms in detail and compares them with each other. Finally, the application of RFID technology in public libraries in China and the United States in the past decade has been investigated. It is found that the number of public libraries in both countries adopting RFID technology is in a rapid growth trend and the use rate of book tags and bookshelf tags is high. The experimental results show that compared with the pure ALOHA algorithm, the frame slot ALOHA algorithm has a significant increase in throughput. When the frame length is equal to the number of tags to be read, the throughput rate reaches the highest 36.78%. As the frame length is closer to the value of the tag to be read, the system efficiency is higher, so in practical applications, the dynamic frame slot ALOHA algorithm can be used, so that the frame length can be adjusted in real time according to the number of tags, which can effectively maintain the highest efficiency in real time.

A reliability and performance GSPN-Based model for anti-collision RFID algorithms under noisy channels in industrial internet of things

The Industrial Internet of Things (IIoT) has the potential to deeply change the technological landscape in factories, transforming the way automation procedures are performed and relevant objects are identified. For that, however, reliability and performance issues have to be considered when providing the expected communication services. When employing Radio-Frequency Identification (RFID) in an IIoT context, previous works have struggled to improve the efficiency of RFID-complaint systems, usually defining mathematical models for planning and quality assessment. Nevertheless, such models are designed based on error-free communications, which are unreal when considering the error-prone nature of wireless communications in industrial plants. Therefore, this article defines a new formal model based on Generalized Stochastic Petri Nets (GSPN) for RFID communications, modelling different possibilities for errors between readers and RFID tags. Since this proposal employs the EPCglobal UHF Class 1 Gen2 parameters as reference, which are already adopted by the Dynamic Frame Slotted Aloha anti-collision protocol for passive RFID systems, this model can be exploited to assess the reliability and performance of different RFID medium access protocols when assuming noisy channels, supporting better comparisons among different algorithms and protocols. Simulation scenarios are defined to present reliability and performance results when assessing RFID tags reading, which are valuable when designing and maintaining IIoT applications.

Offered load estimation in random access multipacket perception systems using the expectation-maximization algorithm

This paper considers offered load estimation in probabilistic dynamic frame slotted ALOHA systems where the receiver can perceive multiple concurrent packets in a slot. This type of random access protocol finds current application in the areas of machine-to-machine communications and tag processing in RFID communications. The perception of multiple concurrent packets happens when a receiver is able to detect the number of received packets or to decode them. In the first case, we talk about multiple packet detection (MPD) whereas in the second we refer to multiple packet reception (MPR). The finite detection capability of MPD or separation capacity of MPR implies that, ideally, whenever the number of simultaneously received packets exceeds a given value M, a collision results and no information about the packets or their number can be extracted. Hence, we are confronted with an incomplete data estimation problem. We reformulate the problem so as to apply the expectation-maximization (EM) algorithm and derive the required iterative equations to obtain a maximum likelihood estimator for the offered load. A numerical example of the algorithm's execution is included and application scenarios are indicated. Simulation studies are presented to show that the proposed estimation method compares favorably with alternative techniques.

An Anti-Collision Scheme for RFID for Patient Tracking Using Linear Interpolation Estimation.

Radio Frequency Identification (RFID) tags are widely used in the healthcare industry for patient tracking. A mainstream RFID implementation is based on a series of readers installed in a fixed location within a hospital or a nursing home and tags are embedded in the clothing worn by patients. Caregivers can readily obtain near real-time location information of individual patients from the tag locations. For implementation in washable clothing tags are often passive such that tag collision is a common problem within co-operation mechanism between tags. Tag anti-collision scheme is there an important consideration that affects the identification effectiveness. To address this issue, this paper proposes a dynamic frame slotted Aloha algorithm based on linear interpolation based estimation that adaptively adjusts the frame length. Simulation results show that the proposed algorithm yields an estimation error below 1.5% achieved in less than 10 iterations, it provides reduction in identification time while reduces the tags leakage probability in a clinical environment where patient tracking is automatically managed.

Multi-packet reception dynamic frame-slotted ALOHA for IoT: Design and analysis

Machine-to-Machine(M2M) Data Collection networks form an integral part of the internet of things wherein a Data Collector (DC) collects data from a large number of nodes. M2M communication protocols should not only be efficient, but they should also be easy to implement. In this regard, Frame Slotted aloha based Medium Access Control protocols have gained popularity for these networks. In the current paper, we propose and analyze the Dynamic Frame Slotted Aloha(DFSA) algorithm for an M2M system with DC having a multi-packet reception (MPR) capability. We develop a stochastic model for the proposed MPR-DFSA algorithm. Based on the Karp-Upfal-Widgerson inequality, we derive asymptotic expressions and bounds for (a) expected number of nodes contending in a given iteration of the algorithm and (b) expectation of the number of iterations the MPR DFSA algorithm takes to finish. Further per-slot throughput and transmission delay of the packet of the MPR-DFSA algorithm have been derived. The analysis is validated through simulation. We compared the proposed MPR DFSA protocol with random access protocols of LTE and Narrowband IoT standards. Finally, we evaluate the performance of MPR DFSA protocol under real-world IoT network scenarios.

Dynamic Frame Update Policy for UHF RFID Sensor Tag Collisions.

The current growing demand for low-cost edge devices to bridge the physical–digital divide has triggered the growing scope of Radio Frequency Identification (RFID) technology research. Besides object identification, researchers have also examined the possibility of using RFID tags for low-power wireless sensing, localisation and activity inference. This paper focuses on passive UHF RFID sensing. An RFID system consists of a reader and various numbers of tags, which can incorporate different kinds of sensors. These sensor tags require fast anti-collision protocols to minimise the number of collisions with the other tags sharing the reader’s interrogation zone. Therefore, RFID application developers must be mindful of anti-collision protocols. Dynamic Frame Slotted Aloha (DFSA) anti-collision protocols have been used extensively in the literature because EPCglobal Class 1 Generation 2 (EPC C1G2), which is the current communication protocol standard in RFID, employs this strategy. Protocols under this category are distinguished by their policy for updating the transmission frame size. This paper analyses the frame size update policy of DFSA strategies to survey and classify the main state-of-the-art of DFSA protocols according to their policy. Consequently, this paper proposes a novel policy to lower the time to read one sensor data packet compared to existing strategies. Next, the novel anti-collision protocol Fuzzy Frame Slotted Aloha (FFSA) is presented, which applies this novel DFSA policy. The results of our simulation confirm that FFSA significantly decreases the sensor tag read time for a wide range of tag populations when compared to earlier DFSA protocols thanks to the proposed frame size update policy.

Anticollision algorithm for radio frequency identification system with low memory requirements

AbstractRadio Frequency Identification (RFID) is recognized as an essential technology for the development of the Internet of Things (IoT) concept. This is due to the possibility of object identification using passive tags which do not require batteries for their operation. Instead, tags are powered by the electromagnetic waves emitted from the reader and then the same electromagnetic wave is used as a carrier to reflect the modulated information about their unique serial number back to the reader. According to the EPCglobal Class‐1 Generation‐2 RFID standard, Dynamic frame slotted ALOHA procedure is used to solve the anticollision problem. Basically, a reader adjusts the frame length for the next reading round based on the estimated number of unread tags. To achieve high reading efficiency, an algorithm with accurate estimation of the remaining number of tags is required. The article shows that for the adjustment of the next frame length, only the number of collisions is relevant. A simple estimator for the frames with 64 slots is designed, and generalized for the frames of any length provided within the EPCglobal Class‐1 Generation‐2 standard. Contrary to existing solutions, which use more tables for storage of the estimated values depending on the frame length, proposed approach requires just one table. Also, the problem of estimation is reduced to dependence on the number of collisions only, while conventional approaches use the number of collisions and successful slots.

LoRaWAN Anti-collision Algorithm Based on Dynamic Frame-slotted ALOHA

With the exponential growth of IoT devices, new challenges have been placed on the scalability and reliability of LoRa networks. At present, the collision problem of the LoRa network is serious. This is because its MAC layer protocol LoRaWAN is mainly based on the pure ALOHA mechanism, which is too simple to handle the collision. The dynamic frame-slotted ALOHA algorithm is optimized on the pure ALOHA algorithm, which can effectively reduce the collision. Therefore, this paper combines the dynamic frame-slotted ALOHA algorithm with LoRaWAN to dynamically divide one cycle into multiple frames. Through the LoRa preamble detection technology, the intra-frame slots are divided into idle time slots, single time slots and collision time slots. According to the number of slots, the optimal frame length of the next frame is estimated. Besides, the paper studies the initial frame length ratio. The simulation experiment is carried out on the LoRaWAN model on ns-3, which verifies that the algorithm can effectively improve the Packet Delivery Ration and System Efficiency.

LC-DFSA: Low Complexity Dynamic Frame Slotted Aloha Anti-Collision Algorithm for RFID System.

With the rapid development of the Internet of Things (IoT), the radio frequency identification (RFID) system becomes increasingly important. Tag identification is a basic problem of the RFID system, whose purpose is to inventory tags. However, in recent years, it requires a very short time for massive tag identification, which brings serious challenges. The traditional Aloha based anti-collision algorithms have disadvantages of either low efficiency or high complexity. Therefore, this article proposes a low complexity dynamic frame slotted Aloha (DFSA) anti-collision algorithm, named LC-DFSA. The reader can estimate the range of tag numbers according to the last frame size, the number of successful slots and the ratio of idle slots. Then the optimal frame size can be calculated. Complexity analysis is deployed in this article, and we validate the correctness of the analysis. Through our simulations, LC-DFSA outperforms other schemes in both the average access efficiency and the algorithm complexity. It also can be conveniently applied to engineering implementations.

Novel tag estimation method by use of Manchester coding in RFID systems

SummaryRadio frequency identification suffers from tag collision issue. ALOHA‐based algorithms are useful and practical groups of tag anti‐collision algorithm among others. Some standards such as EPCglobal Class‐1 Generation‐2 use some kind of dynamic framed slotted ALOHA (DFSA) to cope with tag collision. DFSA efficiency depends on estimating the number of unidentified tags in each identification cycle accurately. So tag estimation is one of the challenging issues in DFSA. In this paper, we use Manchester coding to compute the lower bound of collided tags in a frame and then add α as an additional value to computed value according to the difference between optimal number of collision slots and calculated number of collision slots. Then, we evaluate and compare our method with other proposed methods.

Dynamic frame-slotted ALOHA anti-collision algorithm in RFID based on non-linear estimation

ABSTRACTWe propose an RFID tag anti-collision method using adaptive frame length adjustment. Based on the number of tags identified in the first frame, the original tag population can be estimated by solving a non-linear estimating equation. Subsequent frame lengths can be adaptively adjusted according to the number of remaining tags. The simulation results demonstrate the error rate of the proposed method to be less than 5% – superior to that of existing methods. Compared with the widely used dynamic frame slot ALOHA algorithm – adopted by EPC_C1 G2 standard – tag identification throughput performance increased by 50%.

A novel RFID multi-tag anti-collision protocol for dynamic vehicle identification.

In order to obtain the information of the vehicle tags in adverse traffic conditions, we proposed a novel reservation framework named reservation to cancel idle-dynamic frame slotted ALOHA (RTCI-DFSA) algorithm. Firstly, the framework employed reservation mechanism to remove idle slot, and thus improve the system identification efficiency. Secondly, the vehicle information was identified by the tag serialization polling identification method. The experimental results showed that the proposed RTCI-DFSA algorithm performed better than the traditional frame slotted ALOHA (FSA) and dynamic frame slotted ALOHA (DFSA) algorithms. More specifically, the tag loss rate of the proposed framework is significantly lower than the frame length fixed and conventional dynamic vehicle identification algorithms. In addition, the experimental results demonstrated that the throughput rate of the proposed algorithm increased from 0.368 to 0.6. Besides, the identification efficiency and applicability of the proposed framework were both higher than other tag identification algorithms.

Novel RFID method for faster convergence of tag estimation on dynamic frame size ALOHA algorithms

This paper introduces a novel RFID method for accelerating the tag estimation performance in dynamic framed slotted ALOHA (DFSA) algorithms. Assuming a critical scenario where the number of tags in the interrogation zone is much greater than the initial frame size, the proposed Double-Approximation (DA) method uses, besides the backlog estimation to adjust the size of first frames, a second approximation that successively reduces the tags available to transmit until achieving a faster convergence to the first frame sizes. Once the convergence threshold is achieved, a more accurate tag estimation can be calculated and all temporarily disabled tags become able to transmit again. Simulation results show that all DFSA algorithms implemented with the DA method outperforms the traditional DFSA in terms of throughput and reduction of simultaneous tag signals.