基于G_NSGA-Ⅱ算法的RFID网络规划

针对RFID网络中阅读器冲突问题,在NSGA-Ⅱ算法的基础上提出G_NSGA-Ⅱ算法。对RFID网络规划问题进行数学建模,引入全局存档机制存储精英解,保留性能最佳个体;采用精英保留策略的锦标赛选择方法,确保选择出的个体具有较优秀的性能;同时,引入高斯变异算子,以增加种群多样性,从而避免算法陷入局部最优解。仿真结果表明,G_NSGA-Ⅱ算法所产生的解集质量较好,相较于NSGA-Ⅱ、AW_GA和MOEA/D等3种算法,其在解集的分布性和收敛性上具备明显优势,在解决RFID问题上具备有效性和可行性。

基于改进型白鲸算法的RFID网络规划

随着射频识别(Radio Frequency Identification,RFID)技术的发展,人们对其应用的要求越来越高,在阅读器部署方面的研究也逐渐深入。为了解决规定区域内RFID阅读器位置规划问题,在划定的区域内,以标签覆盖率、阅读器间的碰撞干扰、负载均衡为目标来建立数学优化模型,在白鲸算法的基础上提出了一种改进型白鲸算法。首先,针对标准白鲸算法存在易陷入局部最优、丢失次优解的缺陷,提出了一种更新精英群体机制;其次,为了增强算法的探索能力,加入了反向学习策略;最后,运用该算法来解决RFID网络规划问题。通过在一定环境中放置不同数量集群和随机分布的标签,将改进型白鲸算法与粒子群算法、灰狼算法和标准白鲸算法进行对比。仿真结果表明,在相同环境下,改进型白鲸算法的性能相比粒子群算法平均提高了21.1%,比灰狼算法提高了28.5%,比白鲸算法提高了3.3%,说明该算法相比其他3种算法在搜索精度上具有更好的性能,并通过阅读器优化部署测试,验证了该应用的有效性和可行性。

Random mating mayfly algorithm for RFID network planning

In order to improve robustness and efficiency of the radio frequency identification(RFID)network,a random mating mayfly algorithm(RMMA)was proposed.Firstly,RMMA introduced the mechanism of random mating into the mayfly algorithm(MA),which improved the population diversity and enhanced the exploration ability of the algorithm in the early stage,and find a better solution to the RFID nework planning(RNP)problem.Secondly,in RNP,tags are usually placed near the boundaries of the working space,so the minimum boundary mutation strategy was proposed to make sure the mayflies which beyond the boundary can keep the original search direction,as to enhance the ability of searching near the boundary.Lastly,in order to measure the performance of RMMA,the algorithm is then benchmarked on three well-known classic test functions,and the results are verified by a comparative study with particle swarm optimization(PSO),grey wolf optimization(GWO),and MA.The results show that the RMMA algorithm is able to provide very competitive results compared to these well-known meta-heuristics,RMMA is also applied to solve RNP problems.The performance evaluation shows that RMMA achieves higher coverage than the other three algorithms.When the number of readers is the same,RMMA can obtain lower interference and get a better load balance in each instance compared with other algorithms.RMMA can also solve RNP problem stably and efficiently when the number and position of tags change over time.

基于BSO-BP改进动态帧时隙算法的密集环境下RFID标签读写优化方法

无线射频识别技术作为物联网的关键技术,正在不断发展并广泛应用于我国制造业领域。为了解决大量无线射频识别标签读写时相互竞争信道而产生的数据碰撞现象,需要对标签数量进行准确估计。文章在传统动态帧时隙算法的基础上,利用天牛群搜索算法寻找BP神经网络的最优初始权值和阈值,并将最优值应用到BP神经网络的参数设定中,实现了对标签数量的准确估计。通过实验和企业实际使用RFID绑定电源线的生产效果证明,与传统的动态帧时隙算法相比,所提出的改进算法既保证了读取的准确性,又缩短了读取时间,有效地提高了系统的效率。

RFID network planning based on improved brain storm optimization algorithm

In order to improve the service quality of radio frequency identification(RFID) systems, multiple objectives should be comprehensively considered. An improved brain storm optimization algorithm GABSO, which incorporated adaptive learning operator and golden sine operator into the original brain storm optimization(BSO) algorithm, was proposed to solve the problem of RFID network planning(RNP). GABSO algorithm introduces learning operator and golden sine operator to achieve a balance between exploration and development. Based on GABSO algorithm, an optimization model is established to optimize the position of the reader. The GABSO algorithm was tested on the RFID model and dataset, and was compared with other methods. The GABSO algorithm’s tag coverage was increased by 9.62% over the Cuckoo search(CS) algorithm, and 7.70% over BSO. The results show that the GABSO algorithm could be successfully applied to solve the problem of RNP.

A Precise RFID Indoor Localization System with Sensor Network Assistance

Indoor localization is very critical for medical care applications, e.g., the patient localization or tracking inside the building of the hospital. Traditional Radio Frequency Identification(RFID) technologies are very popular in this area since their cost is very low. In such technologies, each tag acts as the transmitter and the Radio Signal Strength Indicator(RSSI) information is measured from the readers. However, RSSI information suffers severely from the multi- path phenomenon. As a result, if in a very large area, the localization accuracy will be affected seriously. In order to solve this problem, we introduce Wireless Sensor Networks(WSNs) with only a few nodes, each of which acts as both transmitter and receiver. In such networks, the change of signal strength(referred as dynamic of RSSI) is leveraged to select a cluster of reference tags as candidates. Then the fi nal target location is estimated by using the RSSI relationships between the target tag and candidate reference tags. Thus, the localization accuracy and scalability are able to be improved. We proposed two algorithms, SA-LANDMARC, and COCKTAIL. Experiments show that the localization accuracy of the two algorithms can reach 0.7m and 0.45 m, respectively. Compared to most traditional Radio Frequency(RF)-based approaches, the localization accuracy is improved at least 50%.

Distributed Sensor Network Based on RFID System for Localization of Multiple Mobile Agents

This paper presents a distributed wireless sensor network for multiple mobile agents localization. Localization of mobile agents, such as mobile robots, humans, and moving objects, in an indoor space is essential for robot-robot interaction (RRI) and human-robot interaction (HRI). The standard localization system, which is based on sensors installed in the robot body, is not suitable for multiple agents. Therefore, the concept of sensor network, which uses wireless sensors distributed in a specified space, is used in this study. By analyzing related studies, two solutions are proposed for the localization of mobile agents including humans: a new hardware system and a new software algorithm. The first solution focuses on the architectural design of the wireless sensor network for multiple agent localization. A passive RFID system is used, and then the architecture of the sensor network is adapted to suit the target system. The second solution centers on a localization algorithm based on the sensor network. The proposed localization algorithm improves the accuracy in the multiple agent localization system. The algorithm uses the displacement conditions of the mobile agents and the recognition changes between the RFID tags and RFID reader. Through experiments using a real platform, the usefulness of the proposed system is verified.

基于可见光通信及RFID技术的智能车联网系统设计

构建基于可见光通信及RFID技术的智能车联网系统,提高车联网的信息采集能力。设计车联网系统总体架构,主要分为RFID数据无线收发模块、可见光通信模块、信息处理模块。硬件设计,采用RFID技术采集车辆信息,采用可见光通信获取周围车辆信息,通过嵌入式处理器连接车联网系统总线接口与外部设备。软件设计,通过采用分块均衡控制算法实现智能车联网系统的信道优化设计,引入信道切换队列的队头元素计算最佳通信信道,实现智能车联网系统的信道均衡控制。测试结果表明,当节点速度为1 m/s时,本系统的端到端平均时延为33 s,当数据发送率为0.8 m/s时,本系统的吞吐量为189 kb/s。车联网系统对交通安全隐患的平均响应耗时为1.0 s。证明了设计的智能车联网系统应用性能较好,能够有效减少交通安全事故的发生。

Security and privacy threats in RFID traceability network

To address security and privacy issues in radio frequency identification (RFID) traceability networks, a multi-layer privacy and security framework is proposed, which includes four facets: a security model, a communication protocol, access permission and privacy preservation. According to the security requirements that are needed in an RFID system, a security model that incorporates security requirements that include privacy of tag data, privacy of ownership, and availability of tag identity is introduced. Using this model, a secure communication protocol that can be used for anti-counterfeiting, automatic identification and privacy preservation is then developed. In order to manage the number of parties, data records of items, and complicated transitions of access permissions in an item-level traceability context, a well-designed access control protocol is proposed to parties that can prove the physical possession of an item;meanwhile, to address the privacy issues during data sharing in an RFID network, a vision of database systems that take responsibility for the privacy of the data they manage is also presented.

Observing Network Performance and Congestion on Managing Assets with RFID and Cloud Computing

Today, we observe that more and more, radio frequency identification (RFID) technology has been used to identify and track objects in enterprises and institutions. In addition, we also perceive the growing adoption of cloud computing, either public or private, to process and store data from the objects. In this context, the literature does not present an initiative that looks into the network on enterprise-cloud interactions, so neglecting network performance and congestion information when transmitting data to the cloud. Thus, we are presenting a model named ACMA—Automatic Control and Management of Assets. ACMA employs context awareness to control and monitor corporate assets in companies with multiple units. ACMA provides a centralized point of access in the cloud in which interested actors can get online data about each corporate asset. In particular, our scientific contribution consists in considering network congestion to control dynamically the data updating interval from sensors to the cloud. The idea is to search for reliability and integrity of operations, without losing or corrupting data when updating the information to cloud. Thus, this article describes the ACMA model, its architecture, algorithms and features. In addition, we describe the evaluation methodology and the results obtained through experiments and simulations based on the developed prototype.

A novel architecture for cargos location and safety in networked RFID

Using Networked RFID equipped in warehouse or supermarket distribution, Enterprise information system (EIS) can gather and deal with cargos information. Nevertheless, when cargos are in traffic, the Networked RFID can’t monitor the cargos any more as the products tagged aren’t within range of a reader. This paper proposes a solution framework which combines Networked RFID and GPS tracking, and then equip with this system in container to make the cargos monitored even if the cargos are in traffic. This solution can solve the accurate consignments, position tracking and advanced theft happening through drilling holes in container. In addition, customhouse and checkpoint can get an electronic shipment manifest rapidly and safely when a vehicle gets through a checkpoint.

RFID在移动通信领域的应用

射频识别(Radio Frequency Identification,RFID)技术在通信领域取得了很大的发展.从通信行业的发展趋势来看,RFID技术的发展和物际通信市场的拓展,取决于移动通信技术的发展.随着移动通信产品的不断发展,相关业务已趋于饱和,各运营商在网络建设中的差异化程度也越来越低.因此,各运营商要想在激烈的竞争中占得先机,移动通信技术就成了他们关注的重点内容,包括RFID技术在内的自动识别技术又是当下移动通信领域的热门技术之一.在此背景下,主要从RFID技术特点、网络结构、应用领域及应用优势前景等4个方面论述了其应用.

Vehicle Positioning Method Based on RFID in Vehicular Ad-Hoc Networks

With the rapid development of vehicular ad hoc network( VANET) technology,VANET applications such as safe driving and emergency rescue demand high position accuracy,but traditional GPS is difficult to meet new accuracy requirements. To overcome this limitation,a new vehicle positioning method based on radio frequency identification( RFID) is proposed. First RFID base stations are divided into three categories using fuzzy technology,and then Chan algorithm is used to calculate three vehicles' positions,which are weighed to acquire vehicles' accurate position. This method can effectively overcome the problem that vehicle positioning accuracy is not high resulting from the factors such as ambient noise and base distribution when Chan algorithm is used. Experimental results show that the performance of the proposed method is superior to Chan algorithm and 2-step algorithm based on averaging method,which can satisfy the requirements of vehicle positioning in VANETs.

基于ASGSO-BP的RFID定位方法研究

将自适应步长的萤火虫优化(ASGSO)算法与BP神经网络相结合,形成基于ASGSO-BP的无线信道建模方法。采用数据拟合性能较好的ASGSO-BP网络,构建在室内环境下传输无线信号的路径损耗模型,以提高估算信号传输距离的准确性。利用得到的模型和RFID阅读器检测接收到信号强度值的距离,并将该距离用于LANDMARC算法,进行三维空间的室内定位。仿真实验效果显示,采用该方法可显著提升无线信号室内定位的精度及自适应性,对促进智能网联车辆技术的发展具有重要意义。

RFID系统与传感器网络中的数据处理综述

综述了普适计算领域中RFID(电子标签)系统和传感器网络这两个研究热点,阐述了它们的基本概念和技术特性,并对两种系统作了比较和分析,从而引出了数据处理这一核心概念。探讨了两种系统中数据处理需要研究的问题,特别是按照数据处理的流程对两种系统中的数据处理方法进行了较为详细的归纳和分析。

基于RFID技术的仓储管理系统设计

以RFID技术为核心,设计了基于RFID技术的仓储管理系统,与计算机网络技术相结合,集成了完善的软件系统,提供了一套功能齐全、成本低的自动化无线仓储管理系统解决方案,从而实现了物流仓储的无线化、自动化、信息化管理。

超高频RFID读写器组网与协调技术研究

在大规模的RFID技术应用场合,要部署大量的读写器,需要进行读写器网络的规划,为了保证整个读写器网络的通信需求,需要进行读写器之间的协调。本文对超高频RFID读写器组网和协调技术进行了研究,综述了现有的研究成果,并对现有的读写器冲突解决方法进行了比较,讨论了今后的研究方向。

一种基于现场总线的RFID互联系统研究与实现

单个孤立的RFID系统已经不能满足现在的应用需求,依据射频识别系统特点和工作原理,提出了一种基于现场总线技术的RFID互联系统;在研究与实现阅读器射频识别、天线设计和通信功能基础上引入现场总线控制FC(FieldbusControl)技术,提出了基于CAN总线的阅读器节点互联模型,完成了RFID节点硬件电路、电磁兼容性以及应用层通信协议设计。实验表明系统能对各个节点数据进行充分交换和控制,达到了可靠性高、实时性强、扩展灵活、纠检错能力强、布线维护简单、高性价比的设计目标。

基于RFID技术的网络式汽车安防系统的设计

为了降低汽车的失窃率,满足人们对于智能化防盗的需求,设计出了一种融合射频识别技术和全球移动通信网络的汽车安防系统;系统以德州仪器公司的八位车用微控制器STM8AF51AA为控制核心,恩智浦公司的射频读卡芯片MF RC522能迅速识别车主的身份,实现无钥进入和无钥启动功能,热释电红外传感器和振动传感器完成现场监控功能,Simcom公司的GSM模块SIM300DZ实现短信或电话设防和解防,并通过AT命令远程控制汽车的状态;实践表明,与传统的汽车防盗系统相比,系统能唯一识别车主身份,安全性和可靠性提高,实现了智能化防盗和远程控制的统一。

基于速度差分变异粒子群的RFID网络优化

针对RFID网络资源分布不合理问题,建立RFID网络系统优化模型,提出一种带压缩因子和惯性权重的速度差分变异粒子群(VDM-PSO)算法来优化网络中读写器的规划部署。压缩因子和惯性权重保证算法前期搜索的快速性和后期搜索的精确性,速度差分变异操作有效保持粒子群体的多样性,摆脱局部极点的束缚。仿真结果表明,该算法较基本粒子群(PSO)算法群体多样性增强,适应度更佳,能够更好实现网络资源分布。