43 research outputs found

    A collision resolution algorithm for RFID using modified dynamic tree with Bayesian tag estimation

    Full text link
    © 1997-2012 IEEE. 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

    On the optimal configuration of framed slotted ALOHA

    Get PDF

    Frame Size Analysis of Optimum Dynamic Tree in RFID Systems

    Get PDF
    In RFID (Radio Frequency Identification) system, an anti-collision algorithm plays a prominent role in the tag identification process in order to reduce the tag identification delay and enhance the RFID system efficiency. In this work, we present a theoretical analysis of optimal frame size assignment for maximizing the system efficiency of a tree-based anti-collision algorithm, called optimum dynamic tree (ODT) algorithm, for RFID tag identification process. Our analysis indicates that the appropriate frame size for a given number of competing tags should not be set to the same value as the number of tags, which is commonly adopted in the literature. Instead, the frame size should be smaller roughly by a factor of 0.871 to maximize system efficiency. The closed-form for calculating system efficiency is derived and the derived simulation results are in a good agreement with the theoretical one. The exact appropriate frame sizes for the number of tags ranging from 2 to 100 are tabulated and compare the tag-identification time of conventional binary tree and ODT algorithms by using the international standard ISO 18000-6B

    On the Reliability of LTE Random Access: Performance Bounds for Machine-to-Machine Burst Resolution Time

    Full text link
    Random Access Channel (RACH) has been identified as one of the major bottlenecks for accommodating massive number of machine-to-machine (M2M) users in LTE networks, especially for the case of burst arrival of connection requests. As a consequence, the burst resolution problem has sparked a large number of works in the area, analyzing and optimizing the average performance of RACH. However, the understanding of what are the probabilistic performance limits of RACH is still missing. To address this limitation, in the paper, we investigate the reliability of RACH with access class barring (ACB). We model RACH as a queuing system, and apply stochastic network calculus to derive probabilistic performance bounds for burst resolution time, i.e., the worst case time it takes to connect a burst of M2M devices to the base station. We illustrate the accuracy of the proposed methodology and its potential applications in performance assessment and system dimensioning.Comment: Presented at IEEE International Conference on Communications (ICC), 201

    The Challenges and Issues Facing the Deployment of RFID Technology

    Get PDF
    Griffith Sciences, School of Information and Communication TechnologyFull Tex

    Vehicle Cardinality Estimation in VANETs by Using RFID Tag Estimator

    Get PDF
    Nowadays, many vehicles equipped with RFID-enabled chipsets traverse the Electronic Toll Collection (ETC) systems. Here, we present a scheme to estimate the vehicle cardinality with high accuracy and efficiency. A unique RFID tag is attached to a vehicle, so we can identify vehicles through RFID tags. With RFID signal, the location of vehicles can be detected remotely. Our scheme makes vehicle cardinality estimation based on the location distance between the first vehicle and second vehicle. Specifically, it derives the relationship between the distance and number of vehicles. Then, it deduces the optimal parameter settings used in the estimation model under certain requirement. According to the actual estimated traffic flow, we put forward a mechanism to improve the estimation efficiency. Conducting extensive experiments, the presented scheme is proven to be outstanding in two aspects. One is the deviation rate of our model is 50 % of FNEB algorithm, which is the classical scheme. The other is our efficiency is 1.5 times higher than that of FNEB algorithm.Second International Conference, IOV 2015Chengdu, ChinaDecember 19-21, 201
    corecore