ALOHA Algorithm Research Articles

Research on the optimization of the innovation path of university education and teaching management based on the weighted function algorithm of RFID technology

Abstract College education and teaching management are experiencing a transition from traditional modes to informational modes. This paper constructs a management mode for university teaching informatization based on RFID technology and designs the workflow and functions for RFID. For the positioning of student RFID tags on campus, a time-gap ALOHA algorithm is proposed to reduce the collision rate by dividing the processing time of student tags into several time gaps. After obtaining the student tags, an improved K-weighted center-of-mass localization algorithm is proposed for multi-point localization, which makes the weight of multiple known nodes in the process of operation more reasonably distributed through the setting of the weight size. In the simulation test of campus student localization, when the number of beacon nodes is 40, the average error of the K-weighted prime is 6.5%, 4.25%, and 2.1% lower than that of the prime algorithm, weighted prime, and weighted differential prime, respectively.

N-Dimensional Markov Chain Analysis of the Starvation Issue for IEEE 802.15.6 Slotted Aloha Algorithm

N-Dimensional Markov Chain Analysis of the Starvation Issue for IEEE 802.15.6 Slotted Aloha Algorithm

An adaptive frame slotted ALOHA anti‐collision algorithm based on tag grouping

Multi-tag anti-collision is an important problem in radio frequency identification (RFID) application. Solving the problem is of great significance to the RFID technology application and the future internet of things; therefore, an adaptive frame slotted ALOHA anti-collision algorithm based on tag grouping (IGA) is proposed. First, a novel method for estimating the number of tags accurately is proposed. Through theoretical research and the experimental verification, a relationship is obtained between the ratio of the collision time slot in the frame and the average number of tags in each collision slot, which helps us to calculate the number of tags. Second, the method of estimating the number of tags is applied to the IGA algorithm. The reader randomly groups the tags after the number of tags are estimated, and recognises the tags by grouping. In the identification process, the idle time slot is skipped automatically, and the collided tags can be identified with an additional frame until all tags are identified. The simulation results show that the total time slot of the IGA algorithm is relatively small, and the identification efficiency is about 71%, which is 30% better than the the improved RFID anti-collision algorithm and 90% higher than the traditional ALOHA algorithm.

Suffix-based double reader tag movement RFID anti-collision method

At present, some existing tag anti-collision algorithms are used mostly in scenarios of fixed number of tags and they perform poorly in tag moving scenarios. Therefore, this paper proposes a double reader tag movement RFID anti-collision method based on suffix, and through the cloud platform based on cloud computing, the supply chain data sharing is realized. Tag moving scenarios usually use a single reader. The proposed employs double reader to expand the recognition range and also to prolong the recognition time, but there is the problem of repeated recognition. This article proposes a suffix-based bit-slot ALOHA (SBSA) algorithm, where this problem is solved and the time-slot is reduced. In view of the problem that a large number of tags entering into the recognition area of readers lead to the reduction of the recognition efficiency. This article proposes a suffix-based tag group bit-slot ALOHA (STGBSA) algorithm, tag grouping and tag estimation methods are proposed. Complexity analysis is deployed in this article, from the perspective of the tag loss ratio and identification efficiency, the performances of various anti-collision algorithms are evaluated and compared with those of the existing methods. The simulation results show that the method proposed in this paper is better than the existing methods.

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.

Research on hybrid of ALOHA and multi-fork tree Anti-collision algorithm for RFID

Abstract The work aims at the problem of multi-tag collision in RFID system, then analysis the binary tree algorithm and ALOHA and points out their shortcomings, we proposed a Hybrid of ALOHA and Tree (HAMT) Algorithm. The algorithm first uses the DFSA algorithm for tag identification, and dynamically selects the multi-fork tree algorithm for tag identification based on the number of unidentified tags secondly, thus ensuring that the tag is 100% identified, and improves recognition efficiency and shortens recognition time. The results of the simulation show that when the number of tags is about 1000, the recognition efficiency of the HAMT algorithm can reach around 0.72. So the HAMT algorithm can solve the multi-tag collision problem.

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.

Internet of Things technology in mineral remote sensing monitoring

AbstractAt present, the rapid development of the national economy consumes a lot of mineral resources, but the national resource extraction efficiency is low. The traditional prospecting methods consume time, money, and personnel, which cannot meet the national demand for resources in a short time. Therefore, technological innovation is needed to reduce consumption in all aspects. With the continuous development of Internet of Things technology, its application is also more extensive. This paper studies the application of Internet of Things technology in mineral remote sensing monitoring. First of all, this research mainly uses the wireless communication technology in the Internet of Things to achieve data transmission and sharing in a short distance and, second, based on the remote sensing monitoring results of the mine environment to comprehensively understand the mining area and find the suitable mining mineral resources at the fastest speed; finally, the dynamic frame time slot ALOHA algorithm is used to estimate the existing data to ensure the availability of the data. The experimental data show that vector point encryption is performed on the center line of the mine at intervals of 10, 15, 20, 30, and 50 m, respectively, and the dynamic frame slot algorithm is used to calculate the appropriate mine mining curve radius. The experimental results show that the application of Internet of Things technology in mineral remote sensing monitoring can accelerate the mining of mineral resources.

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.

Queue and Channel-Based Aloha Algorithm in Multichannel Wireless Networks

Cross-layer Aloha protocols that exploit the channel diversity when accessing the spectrum became popular in recent years, due to their capability to increase the user rates as compared to classic Aloha-type protocols. Existing algorithms, however, suffer from significant performance degradation in terms of queue load balancing, which makes them inefficient in practical systems. In this letter, we develop a novel queue and channel based Aloha (QCA) algorithm to solve this issue. In QCA, each user trades off between the channel state and the queue state to increase the rate while keeping the queue load small. Strong performance of the algorithm is demonstrated theoretically and numerically.

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.

Fast and Accurate Detection of Unknown Tags for RFID Systems – Hash Collisions are Desirable

Unknown RFID tags appear when tagged items are not scanned before being moved into a warehouse, which can even cause serious security issues. This paper studies the practically important problem of unknown tag detection. Existing solutions either require low-cost tags to perform complex operations or beget a long detection time. To this end, we propose the Collision-Seeking Detection (CSD) protocol, in which the server finds out a collision-seed to make massive known tags hash-collide in the last $N$ slots of a time frame with size $f$ . Thus, all the leading ${f-N}$ pre-empty slots become useful for detection of unknown tags. A challenging issue is that, computation cost for finding the collision-seed is very huge. Hence, we propose a supplementary protocol called Balanced Group Partition (BGP), which divides tag population into $n$ small groups. The group number $n$ is able to trade off between communication cost and computation cost. We also give theoretical analysis to investigate the parameters to ensure the required detection accuracy. The major advantages of our CSD+BGP are two-fold: (i) it only requires tags to perform lightweight operations, which are widely used in classical framed slotted Aloha algorithms. Thus, it is more suitable for low-cost tags; (ii) it is more time-efficient to detect the unknown tags. Simulation results reveal that CSD+BGP can ensure the required detection accuracy, meanwhile achieving $1.7\times $ speedup in the single-reader scenarios and $3.9\times $ speedup in the multi-reader scenarios than the state-of-the-art detection protocol.

Distributed Queueing-Based Random Access Protocol for LoRa Networks

Among many others, LoRa/LoRaWAN is one of the most widely employed technologies to support Internet of Things applications for low-power and long-range wireless devices. LoRaWAN is a medium access control (MAC) layer protocol based on the traditional Aloha algorithm which reveals a great degraded throughput when a large number of devices attempt to communicate over the shared channel at the same time. Aiming at this scalability issue, we propose to introduce the distributed queueing (DQ) algorithm into the MAC protocol over the LoRa physical layer, named DQ-LoRa. The details of DQ-LoRa are provided about the frame structure and access procedure, followed by the performance evaluations on system throughput, average delay, and energy consumption. Our analytical results show that the maximum throughput of DQ-LoRa is independent of the number of devices, and the delay is insensitive to the number of random access minislots for device contending. The numerical computation shows the gain of throughput up to 2.6-fold, and the savings of energy and latency up to 48% and 54%, respectively, in comparing DQ-LoRa with a pure Aloha system.

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.

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.