Dynamic Frame Slotted ALOHA Algorithm Research Articles

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.

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.

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.

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.

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%.

Research on Anti-Collision Algorithm of RFID Tags in Logistics System

In order to solve the problem of RFID tags collision in the current logistics system. Based on the study of existing anti-collision algorithms, a grouped dynamic frame slot with query tree (GDQT) algorithm was designed for a large number of labeling scenarios in logistics management. The GDQT algorithm first estimates the number of tags that have not been identified after each round of identification by the tag estimation algorithm, if less than or equal to 354, the tags were first identified using the dynamic frame slot ALOHA (DFSA) algorithm., and then using the query tree algorithm (QT) for the remaining tags identification. If the number of unrecognized tags was greater than 354, the tags should be first grouped, and then DFSA and QT would be used for tags identification. The simulation results showed that GDQT algorithm can improve system throughput rate and keep throughput rate at around 0.82, which is 300%, 120%, 50% higher than the DFSA algorithm, GDFSA algorithm and AHT algorithm respectively. Therefore, The GDQT algorithm has a good application prospect in the logistics system.

A Novel Cross Layer Anti-Collision Algorithm for Slotted ALOHA-Based UHF RFID Systems

Reducing collisions in UHF RFID systems is a crucial problem. In most anti-collision designs, the reader has to estimate the number of tags within its reading range during the interrogation process. Most of the approaches estimate the number of tags with observations in multiple time slots. Since estimation error varies along with the initial frame length and the number of tags, system efficiency is affected by both of them. To reduce the sensitiveness to them and improve system efficiency, we propose a novel MAC-PHY cross-layer anti-collision algorithm based on Bayesian inference. Specifically, each frame is allowed to end at an early stage and a slot-by-slot estimator is proposed. Benefit from its slot-by-slot nature, system efficiency is more stable and independent on the initial frame length and very close to the upper bound of dynamic framed slotted ALOHA (DFSA) algorithm. The performance of the proposed method is compared with the state-of-the-art algorithms through numeric simulations. The results show that the proposed solution significantly outperforms the compared ones.

A rapid anti-collision algorithm with class parting and optimal frames length in RFID systems

Several dynamic frame-slotted ALOHA (DFSA) methods are suggested to resolve the collision problem in radio frequency identification systems. This paper proposes a rapid DFSA-based algorithm for tags identification. The above-stated algorithm is based on adaptive class parting technique to select the optimal frames length. The selection of the best frame length is a major research factor to be used for dynamic frame slotted ALOHA algorithm. To get the best frame length in DFSA protocol, we classified the tags into the some groups. Each group of tags is determined by same prefixes. The main objectives of the new algorithm are to improve the tags identification time and to increase the reader energy efficiency. The ideal frame size has to be fixed to 2 times of the total of tags bit length if the ratio among collision-slot and empty-slot is 5. Observing the results clarifies that the algorithm in this paper offers a reading rapidity of up to 400 tags/s and can achieve time-saving identification up to 15–20% in comparison to the traditional DFSA. The rapid DFSA anti-collision algorithm has a number of merits such as compatibility with ISO 18000-6, better system performance and ease of implementation.

A cooperative Bayesian and lower bound estimation in dynamic framed slotted ALOHA algorithm for RFID systems

SummaryA novel estimation scheme that combines Bayesian and lower bound estimating radio frequency identification tag population size is proposed. The developed methodology is based on the fusion between the Bayesian and lower bound estimating techniques. It turns out that the fusion rule is built up thanks to an existing linear relationship between the cited techniques. Simulation results show that the developed technique significantly improves the accuracy of the estimating tag quantity and presents less estimation error. Also, the resulting advanced dynamic framed slotted ALOHA protocol considerably improves the performance and efficiency of the radio frequency identification anti‐collision compared with the most recent protocols using others estimating methods.

Performance Analysis of M2M Data Collection Networks Using Dynamic Frame-Slotted ALOHA

We are witnessing an explosion in the growth of the number of connected devices, with the consequent increase of their share in global energy consumption. Thus, it is mandatory that we employ green networking technologies for Internet of Things and machine to machine (M2M) networks. In M2M data collection networks, hundreds or thousands of devices communicate with a data collector (DC). In this regard, dynamic frame slotted Aloha (DFSA) has gained popularity as an energy efficient MAC protocol for M2M data collection networks. In this paper, we carry out performance evaluation of DFSA algorithm. First, we derive analytical bounds on the performance of DFSA. To this end, we employ the properties of binomial distributions and Karp–Upfal–Widgerson inequality. Furthermore, we propose a simple MAC protocol based on DFSA, and analyze the protocol under saturated traffic condition. Using a mathematical model for our proposed protocol, we derive closed form expressions for system throughput, packet delay, and the energy efficiency of the node and the DC. The analysis is validated through extensive simulation.

Capture-aware Bayesian RFID tag estimate for large-scale identification

Dynamic framed slotted Aloha algorithm is one of popular passive radio frequency identification U+0028 RFID U+0029 tag anticollision algorithms. In the algorithm, a frame length requires dynamical adjustment to achieve higher identification efficiency. Generally, the adjustment of the frame length is not only related to the number of tags, but also to the occurrence probability of capture effect. Existing algorithms could estimate both the number of tags and the probability of capture effect. Under large-scale RFID tag identification, however, the number of tags would be much larger than an initial frame length. In this scenario, the existing algorithm U+02BC s estimation errors would substantially increase. In this paper, we propose a novel algorithm called capture-aware Bayesian estimate, which adopts Bayesian rules to accurately estimate the number and the probability simultaneously. From numerical results, the proposed algorithm adapts well to the large-scale RFID tag identification. It has lower estimation errors than the existing algorithms. Further, the identification efficiency from the proposed estimate is also higher than the existing algorithms.

Collision Detection and Signal Recovery for UHF RFID Systems

In this paper, we present a novel high-throughput anti-collision algorithm for passive ultrahigh-frequency (UHF) radio-frequency identification (RFID) systems. Our algorithm utilizes signal recovery techniques of collided tag signals to both recover tag communications and obtain an accurate count of all tags in the field. Passive UHF RFID systems are used for long-range passive communications for applications including supply chain management and electronic tolling. Anti-collision algorithms are used to ensure successful RFID tag communications due to the likelihood of multiple tags being in the field and attempting to communicate simultaneously. The limited on-tag functionality necessitates the use of simple anti-collision algorithms such as a dynamic frame slotted Aloha (DFSA) algorithm. With our novel collision detection and signal recovery anti-collision algorithm, the RFID reader can retrieve multiple valid communications from each collided slot in a DFSA-based anti-collision protocol, while our algorithm allocates an optimal number of slots resulting in more collided but recoverable slots and fewer empty slots. Our algorithm achieves a nearly 100% throughput improvement with an expected throughput of 0.85 compared with an expected throughput of 0.426 for a standard DFSA algorithm. The reader receiver with the proposed algorithm is implemented in a field-programmable gate array and the whole reader system is verified using the communication tests with commercial tags. According to the synthesized results in an SMIC 0.13- $\mu \text{m}$ CMOS technology, the collision detection and signal recovery module consumes about 135k GE. Note to Practitioners —Signal recovery methods are capable of extracting information from collided signals. In this paper, we introduce and analyze a signal recovery method based on the voltage histogram of the received signal. Both the original signals and the number of collided signals are recovered. The information of tags is used by our novel algorithm to increase the system throughput in DFSA-based anti-collision algorithms. The recovered signals allow our algorithm to directly obtain the tag identifier. By determining the number of collided signals, our algorithm is able to calculate an accurate estimate of the total number of tags in the reader’s field. With signal recovery and an accurate tag count, our algorithm is able to reduce the total number of slots needed to identify all tags, thereby increasing the throughput. We present a novel frame length optimization method that increases throughout by shrinking the number of slots, thereby intentionally causing collisions and reducing the total number of empty slots. In addition, we present a hardware implementation of our novel method that is suitable for integration into RFID readers. When the signal strengths of the tags in collision in the in-phase or quadrature path are not close to each other, the performance of our method is much better than that of the traditional method in which the collision signal is treated as ineffective and ignored.

A Power Control and Anticolision Mechanism for RFID Systems

RFID (Radio Frequency IDentification) applications require identification of large number of tags, which results in increased collisions and degradation in the performance of traditional DFSA (Dynamic Frame slot ALOHA) algorithms. This paper proposes a power control mechanism to estimate the amount of tags in RFID networks. The mechanism is based on the division of the interrogation zone in sub-areas called clusters. This division is used to interrogate in a single slot all tags of a cluster, perform measurements of RSSI and, with it, estimate the amount of tags per cluster. The mechanism is simulated and evaluated using our own simulator developed in C/C ++ programming language. We compared the results of number of slots, identification time and energy consumption with that obtained from the use of the optimal DFSA algorithm and Q algorithm of the EPCglobal standard. From the simulation results, one can see that the proposed mechanism provides performance 99% close to the ideal DFSA in dense networks, where there are large amount of tags.

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.

An Effective Frame Breaking Policy for Dynamic Framed Slotted Aloha in RFID

The tag collision problem is considered as one of the critical issues in RFID system. To further improve the identification efficiency of an UHF RFID system, a frame breaking policy is proposed with dynamic framed slotted aloha algorithm. Specifically, the reader makes effective use of idle, successful, and collision statistics during the early observation phase to recursively determine the optimal frame size. Then the collided tags in each slot will be resolved by individual frames. Simulation results show that the proposed algorithm achieves a better identification performance compared with the existing Aloha-based algorithms.

Flood Diversion Algorithm for Anticollision in RFID System

Radio frequency identification (RFID) provides a contactless approach for object identification. If there are multiple tags in the interrogation zone of a reader, tag collision occurs due to radio signal interference. To solve tags identification collision and improve identification efficiency in RFID system, a flood division anticollision (FDAC) algorithm has been presented. Firstly, the algorithm launches an estimation of the number of tags and according to the estimation result decides whether a flood diversion processing needs to be started or not. Secondly, when the flood diversion processing needs to be done, all tags are grouped and assigned to different models in which the tags are to be processed and identified in parallel. Thirdly, in the identification processing, for reducing data transmission, the reader needs only to send a three-dimensional-vector command to tags, tags respond to the command with part of collision-bit parameters, and stack and queue are adopted to store precious request command and tags' ID to avoid repeatedly transmitting them between the reader and the tags. Simulation experiment results show that FDAC is superior to the dynamic frame slotted (DFS) Aloha algorithm, the binary-retreat tree algorithm (BRT) and the dynamic binary-search tree (DBST) algorithm, in the performances of data bits transmission, identification time delay, and energy consumption by the reader.

An Improved RFID Tag Collision Algorithm

Tag collision is a very important research direction in the RFID system. Probabilistic solving algorithm is one of the important way to solve the tag collision, dynamic frame slot ALOHA (DFSA) algorithm is more commonly used at present and the probabilistic algorithm with better effect. This paper proposes an Advanced DFSA (ADFSA) which is based on a dynamic frame slot ALOHA algorithm, combined with multiplier factor and grouping thoughts. the algorithm is simple, at the same time, the simulation results show that IDFSA algorithm has better performance.

Group improved enhanced dynamic frame slotted ALOHA anti-collision algorithm

With the development of information technology and declining in the cost of tags, radio frequency identification (RFID) system has become more and more popular, which has been widely used in a lot of areas, such as logistics tracking, animals identification, medicine, electronic toll collection, inventory, asset management, manufacturing, etc. However, when we use RFID technology to identify the objects, tag collision is one of the important factors to influence the identification efficiency. Currently, Aloha-based algorithm is one of the popular anti-collision algorithms which performs well when the number of tags is small. But it is not very efficient for cases with large number of tags and some areas which tags' number can be estimated, such as warehouse, supermarket, the production lines of smart factory and so on. So in this paper, we proposed a new anti-collision algorithm called group improved enhanced dynamic frame slotted ALOHA (GroupIEDFSA) by estimating the number of unread tags first, comparing the maximum frame size and dividing tags into groups when the number of tags which are activated is large. What is more, compared with enhanced dynamic frame slotted ALOHA (EDFSA) algorithm in the process of identification, GroupIEDFSA algorithm will combine new group based on the unread tags' number. Simulation results show that the efficiency of GroupIEDFSA algorithm system improves by 20 % in time and over 50 % in rounds than EDFSA algorithm in the standard mode, and increases by 1 % in time when we used fast mode.