An optimized dynamic frame slotted ALOHA anti-collision algorithm

There are two kinds of collision. They are reader collision and tagcollision. The way to solve the collision called the anti-collision algorithm. Comparing with the reader collision, the tag collision take place in a higher probability and the problem of tag anti-collision is considered to be an important issue to resolve. When more than one tag in the reader area and send datum to the reader at the same time, the signal of the tags will interferes each other and the tags will not be able to be identified. We call it tag collision. It belongs to the mufti-target identification problems. At present probability algorithms used to solve tag collision are all based on the ALOHA algorithm for research and Dynamic Frame Slotted ALOHA (DFSA) algorithm is the more common and better-performing probabilistic algorithm. The focus of this algorithm is how to estimate the number of tags within the scope of reader effecting and according to this estimated value to adjust the length of the frame dynamically to achieve maximum system efficiency. This paper presents a new algorithm IEDFSA (Improved Enhanced Dynamic Frame Slotted ALOHA) based on DFSA and combining with multiplying factor and grouping mind. The IEDFSA algorithm is easy to carry out and the simulation results show that IEDFSA has better performance.

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.

At present probability algorithms used to solve tag collision are all based on the ALOHA algorithm for research and improvement. Dynamic Frame Slotted ALOHA (DFSA) algorithm is the more common and better-performing probabilistic algorithm. The focus of this algorithm is how to estimate the number of tags within the scope of reader effecting and according to this estimated value to adjust the length of the frame dynamically to achieve maximum system efficiency. This paper presents a new algorithm IDFSA (Improved Dynamic Frame Slotted ALOHA) based on DFSA and combining with multiplying factor and grouping mind. The IDFSA algorithm is easy to carry out and the simulation results show that IDFSA has better performance.

Aiming at the problem of tag conflict in the RFID system, an improved algorithm based on dynamic framed slotted ALOHA algorithm is proposed. In this algorithm , when the recognition of a frame length is still not finished, according to the existing conflict timeslot and free timeslot inside of frame, frame length can adjusted in advance, furthermore a new frames recognition process is began, which can improve the recognition efficiency of the existing algorithm, increase throughput. The performance simulation experiment shows that the improved algorithm has more advantage than dynamic slotted ALOHA algorithm.

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.

Due to collision and mobile problems, it is difficult to use a single reader to identify a large number of mobile tags successfully. In this paper, a new anti-collision scheme is proposed, which combines the tag anti-collision algorithm and multiple reader deployment to solve the mobile tag collision problem. This scheme adopts grouped dynamic frame slotted ALOHA algorithm based on CDMA to deal with the collision which is caused by that large amounts of tags response to the reader. And it adopts the power control algorithm based on cellular model to deal with the collision between the readers. The simulation results show that the total number of slots needed by the tag anti-collision algorithm is less than other similar algorithms; the cumulative adjustment times of reader anti-collision algorithm are less than other similar algorithms, and the algorithm is more stability. It has certain application value in practical engineering.

RFID system tags collision occurs when multiple tags are energized by the RFID tag reader simultaneously. Therefore, it is important for RFID readers to make use of the anti-collision algorithms to enable a single reader to read multiple tags in the reader's field. Here, we report on the comparison of different ALOHA anti-collision algorithms, and propose an enhanced tag estimation technique for dynamic framed slotted ALOHA algorithm. Simulation results show that the proposed technique is able to maintain the throughput of 0.36 as the frame size changes dynamically up to 1024 tag population.

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.

Passive UHF RFID systems using Dynamic Frame-Slotted ALOHA (DFSA) adjust the frame size according to the number of tags, but frame size N is equals to 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</sup> and cannot be adjusted exactly to the number of tags to be identified. In this paper, we propose an optimal Aloha algorithm (ODFSA), which uses probabilistic approach for tags to access the frame. The Query or Query Adjust packet contains both the parameter Q and P called frame access probability, which represents the ratio of number of active tags in the current frame to the estimated total number of tags which remain to be identified in the system. Estimation of number of unread tags is updated after end of each frame; parameters Q and P are calculated and informed at the beginning of each frame. Mathematical analysis and computer simulations show that the proposed Aloha achieves maximum system efficiency, utilizes less number of slots compared with other algorithms and also takes less identification time.

Minimizing the reading time of the tag population is a critical issue in radio-frequency identification (RFID) systems. The usual approach to reduce the reading time is to select the frame size attaining the highest throughput per frame. Previous studies have focused on the frame length calculations using the conventional framed slotted ALOHA (FSA) algorithms. In such systems, only the answer of a single tag is considered as a successful slot, and if multiple tags respond simultaneously, a collision occurs. Then all the replied tags are discarded. However, modern systems have the capability of recovering this collision and convert the collided slot into a successful slot. Recent studies focused on calculating the optimal frame length taking into consideration the collision recovery probability. However, these studies have assumed a constant collision recovery probability coefficient, i.e., the probability to recover one tag from i collided tags per slot is constant regardless the value of i. In this work, we propose a novel closed-form solution for the optimal FSA frame length which considers the differences in the collision recovery probabilities. The values of the collision recovery coefficients are extracted from the physical layer parameters. Timing comparisons are presented in simulation results to show the mean reduction in reading time using the proposed frame length compared to the other proposals.

A priori knowledge of the number of tags is crucial for anti-collision protocols in slotted UHF RFID systems. The number of tags is used to decide optimal frame length in dynamic frame slotted ALOHA (DFSA) and to adjust access probability in random access protocols. Conventional researches estimate the number of tags in MAC layer based on statistics of empty slots, collided slots and successful slots. Usually, a collision detection algorithm is employed to determine types of time slots. Only three types are distinguished because of lack of ability to detect the number of tags in single time slot. In this paper, a physical layer algorithm is proposed to detect the number of tags in a collided slot. Mean shift algorithm is utilized, and some properties of backscatter signals are investigated. Simulation results verify the effectiveness of the proposed solution in terms of low estimation error with a high SNR range, outperforming the existing MAC layer approaches.

We propose the ALOHA-based Dynamic Framed Slotted ALOHA algorithm (DFSA) using proposed Tag Estimation Method (TEM) which estimates the number of tags around the reader. We describe the conventional Tag Estimation Method and Dynamic Slot Allocation (DSA), which is the method to dynamically allocate the frame size according to the number of tags. We compare the performance of the proposed DFSA algorithm with the conventional algorithms using simulation. According to the analysis, the proposed DFSA algorithm shows better performance than other conventional algorithms regardless of the number of tags because the proposed algorithm has lower complexity and better delay performance.

Dynamic frame slotted Aloha (DFSA) has been widely adopted to solve the anticollision problem in a radio frequency identification (RFID) system. In a DFSA procedure, the interrogator needs to continuously estimate tag backlog and select a new frame length for identifying the backlog. Intuitively, the accuracy of the tag estimator will affect the read performance. Hence, a considerable amount of research effort has been invested to improve the accuracy of backlog estimation. The improvement in general comes at the expense of large computation load and may lead to a serious challenge if one needs to implement such a kind of estimators in a real RFID system. This paper analyzes the influence of estimation error on read performance. Based on the analysis, we propose a feasible and easy-to-implement anticollision algorithm. Our proposed algorithm can achieve a normalized throughput of 35% that is very close to the theoretical maximum 36.1% for an EPCglobal UHF Class-1 Generation-2 system. The easy-to-implement advantage of our algorithm comes at the expense of only 1% reduction in normalized throughput as compared with the case where maximum throughput can be obtained. The results obtained are useful in designing fast and efficient interrogators. Note to Practitioners - A fast and efficient anticollision algorithm is required in many applications such as warehouse and supply chain management. Since most RFID interrogators are built with a single-chip microprocessor, whose computation ability or memory is limited. From the implementation point of view, a feasible algorithm should consider the compromise between complexity and performance. In order to easily implement the anticollision algorithm in a real RFID system, the proposed algorithm is based on a simple but sufficiently accurate method rather than complex models. The results obtained can be useful for the industry to develop fast and efficient RFID interrogators.

Comprehensive review of the research of one kind of anti-collision algorithms and analysis of their disadvantages were provided.Based on the analysis of the frame size adjusting method of the most in common use branch dynamic framed slotted Aloha algorithm,this paper brought forward an improved resolution by dynamically adjusting the frame size and group division,which can consumedly enhance the system efficiency and its stability.

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.