RFID系统阅读器反碰撞算法的改进研究

本文研究了RFID系统中阅读器冲突问题,分析了三种阅读器冲突问题,并给出了冲突模型。对目前已有的阅读器防冲突算法进行了分析比较,并在Pulse算法的基础上提出了一种改进型的算法,降低了阅读器在控制通道里的冲突概率并提高了阅读器阅读速率,对该算法的理论分析表明,该算法适合于移动式阅读器网络或手持式阅读器的应用。     

基于模糊控制的和积算法在图形着色中的应用

采用集中式遗传算法解决图形着色问题存在遗传算子影响群体多样性而使算法本身容易陷入局部收敛等情况,针对该问题,A.Farinelli等提出了利用和积算法解决图形着色问题.然而基于和积算法的着色图的初始冲突教会因图的复杂度或结点规模的加大而大幅增多,从而降低了和积算法效率.为此提出了基于模糊控制的和积算法,利用模糊控制减少着色图中的冲突.实验结果表明,与和积算法及集中式的遗传算法相比该算法在着色效果和算法效率上都有了显著的提高.     

带冲突图的着色旅行商问题模型与算法

着色旅行商问题是多旅行商问题的一个重要变种，它被广泛地应用于带有重叠区域的多机工程系统。现有的着色旅行商问题难以有效应对带冲突的场景，这种冲突通常表现为两个城市不允许被同一旅行商访问。受带冲突图的组合优化问题的启发，提出了带冲突图的着色旅行商问题，且给出了其形式化的表达。带冲突图的着色旅行商问题是一个NP难问题，精确算法求解器CPLEX仅能在小规模问题实例上获得问题的最优解。为了求解更大规模的实例，提出了一个有效的模因算法。该模因算法采用了自适应大规模邻域搜索算子。对比模因算法和精确算法，模因算法在20个小规模实例中的9个结果更好，在18个实例上展现了其远超精确算法的求解速度。而比较模因算法和其他启发式算法，模因算法在全部14个中等规模实例上均取得了更好结果。此外，消融实验结果验证了模因算法中自适应大规模领域搜索算子的有效性。     

射频识别系统中的多标签防冲突算法

在RFID系统中,当阅读器作用范围内有多个标签同时向阅读器发送数据时,就会产生冲突,需要防冲突算法解决该问题.本文主要是针对二进制搜索算法进行详细的研究,并提出一种改进算法的实现方法.     

多寄存器组网络处理器上的寄存器分配技术

针对传统的图着色寄存器分配算法不能直接处理网络处理器的操作问题,提出了一种多寄存器组网络处理上的寄存器分配技术．在依次分析了一个符号寄存器可能位于哪些寄存器组？如果没有候选组,该如何解决这种冲突？如果有多个候选组,该选用哪个组等问题的基础上,通过将这些方法与图着色寄存器分配算法相融合,在IXP上实现了这种多寄存器组的寄存器分配,提高了它的可编程性．这种方法也可运用到其它具有类似寄存器结构的处理器上．     

基于粘贴和删除系统的图着色问题分析

图着色问题是图与组合优化中的一个NP-完全问题．现有算法在求解图着色问题时,计算复杂性随着待解问题规模的增大呈指数增长．粘贴系统和删除系统是分别基于粘贴运算和删除运算的两种语言生成器．文中将图着色问题和图的坏边数结合起来,将图着色问题转化成搜索最长序列的问题,然后利用粘贴系统和删除系统的并行性,得到了图的色数及其所有色类．与已有求解图着色问题的DNA算法相比,新的算法具有较低的复杂性．     

一种新的RFID标签识别防冲突算法

在 RFID 网络通信中, 当多个标签同时回应阅读器的查询时, 如果没有相应的防冲突机制, 会导致标签到阅读器的通信冲突, 使得从标签返回的数据难以被阅读器正确识别. 防冲突算法是阅读器快速、正确获取标签数据的关键. 一种被称为基于栈的 ID-二进制树防冲突算法 (Stack-based ID-binary tree anti-collision algorithm, SIBT) 被提出, SIBT 算法的新颖性在于它将 n 个标签的 ID 号映射为一棵唯一对应的 ID-二进制树, 标签识别过程转化为在阅读器中创建ID-二进制树的过程. 为了提高多标签识别效率, 阅读器使用栈保存已经获取的ID-二进制树创建线索, 用计数器保存标签在该栈中的深度. 理论分析和仿真结果表明 SIBT 算法的性能优于其他基于树的防冲突算法.     

图着色问题的启发式搜索蚂蚁算法

针对经典的图着色问题,该文在随机序列启发式搜索求解的基础上,引进蚂蚁算法优化思想,设计了一种新型算法,有效地避免了启发式搜索易陷入局部极小的缺陷。通过给地图着色和仿真实验结果表明,该方法对图着色问题的求解是可行、有效的,且具有通用性。     

RFID环境下利用通报机制的分布式阅读器防冲突算法

针对无线射频识别(RFID)单元的分布情况可能会导致出现多种类型的冲突以及现存算法的系统成本较高等问题,提出多个数据通道完成阅读器和标签之间的通信,是一种分布式算法。在接受问询流程中,阅读器首先等待一个伪随机时间,然后检测两个序列,如果这两个条件都不满足,阅读器将会等待伪随机时间后再次尝试。在接受过程中,如果存在任何可利用的数据通道,阅读器就会选取不同的数据通道。该设置可以确保避免发生隐藏和暴露终端问题。实验利用范围传播损耗模型和NS3的802.11 Wifi模型在网络模拟器NS3中对算法进行整合。与邻域友好型防冲突算法(NFRA)、多通道MAC协议(MCMAC)算法和冲突避免(Dica)的分布式算法相比,实验结果显示提出的算法降低了标签识别过程中花费的时间,而且集中控制过程额外的空间成本更低,因此在最小化网络开销的情况下增加了成功询问的比例。     

基于混合粒子群的RFID网络的优化部署*

在RFID网络系统中,贴有标签的物品可能随机地布置着,针对如何有效地放置阅读器,使得阅读器可以读取多个标签信息同时减小冲突的问题,建立了RFID网络系统的优化模型,提出了一种混合粒子群算法来优化部署阅读器的位置。实验结果表明,混合粒子群算法分别比传统的粒子群(PSO)和遗传算法(GA)在收敛速度和寻优能力上具有更好的性能,体现出混合粒子群算法的优越性。     

RFID系统识读器冲突问题研究

介绍RFID系统中识读器的冲突问题,并提出随着时间分配频率给无线射频识别（RFID）识读器的方法,以便减少它们之间的干扰。我们通过图色的方法建立了问题模型及其相应的变量表达式。     

Optimal scheduling-based RFID reader-to-reader collision avoidance method using artificial immune system

In radio frequency identification (RFID) systems, communication signals from one desired reader is subject to interference from the other adjacent readers operating at the same time, so the reader-to-reader collision problem occurs. Many RFID reader collision avoidance methods have been developed, such as coverage-based methods, control mechanism-based methods and scheduling-based methods. In the scheduling-based methods, how to allocate frequency channels and time slots for the RFID reader network is emphasized. In this case, the RFID reader collision avoidance problem is transferred as an optimal scheduling problem, which can be solved by analytical methods and intelligent algorithms. Artificial Immune System (AIS) optimization is an emerging heuristic method derived from the human immune system. Due to its powerful global searching capability, AIS has been widely applied to scientific and engineering problems. This paper attempts to formulate the reader-to-reader collision problem (R2RCP) and its scheduling-based reader-to-reader collision avoidance model (R2RCAM), and proposes an improved AIS optimization for resource allocation (RA-AIS) in R2RCAM. Within the proposed RA-AIS optimization, the candidate antibody is constructed by using frequency channels and time slots, and in the mutation phase, the candidate antibody evolves dynamically according to its corresponding readers’ interfering power. The proposed RA-AIS optimization is examined on a series of numerical experiments to evaluate the effects of time slots, frequency channels, and transmitting power. Moreover, a group of comparative experiments are also arranged. The experimental results demonstrate that the proposed RA-AIS optimization is an effective method for R2RCAM, and performs better in searching the maximum interrogation area than other algorithms, such as random method (RM), genetic algorithm (GA), particle swarm optimization (PSO) and the canonical artificial immune system optimization (opt-aiNet).     

基于图论的射频识别阅读器防碰撞算法

射频识别（RFID）系统的运行往往需要多个阅读器,以保证覆盖整个目标区域。在密集的阅读器的环境中,由于阅读器之间存在相互干扰,会影响整个RFID系统的工作效率,降低识别效率。针对上述问题,提出一种新的基于图论的阅读器防碰撞算法。首先把阅读器网络看成简单图,以时隙对阅读器分组,同时隙阅读器为一组,相邻阅读器分配不同的时隙,以解决阅读器因读取范围交叉重叠而引起的干扰;同时考虑组内阅读器的频率干扰问题,同样以频率对组内阅读器再分组,同频率阅读器为一组,相邻阅读器分配不同频率,以解决因干扰范围过大而引起的频率碰撞问题;然后根据分组信息,中央服务器通过配置命令将时隙和频率资源调度分配给每个阅读器;最后通过时序命令控制每组阅读器的工作顺序。仿真结果显示,相比邻近友好型防碰撞（NFRA）算法,该算法平均工作效率提升了6.5个百分点;阅读器数量为1000时系统工作效率提升了9.5个百分点。新算法能优化给定时间内工作阅读器的数量,减少闲置等待的阅读器数量。     

一种井下RFID定位系统的读卡器防碰撞算法

随着技术的进步,RFID(射频识别)已在煤矿进下定位里得到了应用。由于频率资源有限,读卡器间往往存在频率干扰,将导致RFID定位系统出现读卡器碰撞的问题。分析了读卡器碰撞的两种情形,提出了基于Q学习的仿碰撞算法,并进行了仿真测试。测试结果表明,读卡器碰状问题得到了有效控制,也说明提出的防碰撞算法是有效、可行的。     

Comparative performance analysis of various artificial immune networks applied to RFID reader-to-reader collision avoidance

Within a radio frequency identification (RFID) system, the reader-to-reader collision problem may occur when a group of readers operate simultaneously. The scheduling-based family, as one branch of RIFD reader collision avoidance methods, focuses on the allocation of time slots and frequency channels to RFID readers. Generally, the RFID reader-to-reader collision avoidance model can be translated as an optimization problem related with the communication resource allocation by maximizing the total effective interrogation area. Artificial immune networks are emerging heuristic evolutionary algorithms, which have been broadly applied to scientific computing and engineering applications. Since the first version of artificial immune networks for optimization occurred, a series of revised or derived artificial immune networks have been developed which aim at capturing more accurate solutions at higher convergence speed. For the RFID reader-to-reader collision avoidance model, this paper attempts to investigate the performance of six artificial immune networks in allocating communication resources to multiple readers. By following the spirits of artificial immune networks, the corresponding major immune operators are redesigned to satisfy the practice of RFID systems. By taking into account the effects of time slots and frequency channels, respectively, two groups of simulation experiments are arranged to examine the effectiveness of different artificial immune networks in optimizing the total effective interrogation area. Besides, a group of examination is executed to investigate the performance of six algorithms in solving different dimensionality of solution space in reader collision avoidance model. Meanwhile, a single group of simulation experiments are arranged to examine the computational efficiency of six artificial immune networks. The results demonstrate that six artificial immune networks perform well in searching the maximum total effective interrogation and are suitable to solve the RFID reader-to-reader collision avoidance model.     

A Hopfield network learning method for bipartite subgraph problem

We present a gradient ascent learning method of the Hopfield neural network for bipartite subgraph problem. The method is intended to provide a near-optimum parallel algorithm for solving the bipartite subgraph problem. To do this we use the Hopfield neural network to get a near-maximum bipartite subgraph, and increase the energy by modifying weights in a gradient ascent direction of the energy to help the network escape from the state of the near-maximum bipartite subgraph to the state of the maximum bipartite subgraph or better one. A large number of instances are simulated to verify the proposed method with the simulation results showing that the solution quality is superior to that of best existing parallel algorithm. We also test the learning method on total coloring problem. The simulation results show that our method finds optimal solution in every test graph.     

A consensus-function artificial neural network for map-coloring

A harmony theory artificial neural network solution to the map coloring problem is presented. Map coloring aims at assigning a unique color to each area of a given map so that no two adjacent areas receive identical colors. The harmony theory implementation is able to determine whether the map coloring problem can be solved with a predefined number of colors as well as which is the smallest number of colors that can solve the map coloring problem. The present implementation directly encodes the given problem into the artificial neural network so that a solution is represented simply by node activation. Additionally, the consensus function of harmony theory produces a quick and definite solution to the colorability problem, obviating the need for manual validation of the result.     

基于IRCM的抗阅读器冲突协议

在射频识别技术RFID（Radio Frequency Identification）技术的应用中,不同阅读器的信号之间互相干扰造成的阅读器冲突问题是制约系统性能的主要瓶颈之一,尤其在阅读器密集分布和移动的环境中,问题更为突出。结合现有多种抗冲突方法的优点,提出一种针对多信道的、阅读器密集分布的RFID系统的基于IRCM的抗冲突协议。仿真表明在多信道、阅读器密集分布的RFID系统中该协议能显著提高系统效率。     

A centralized and aligned scheduler for passive RFID dense reader environments working under EPCglobal standard

Passive RFID systems with several reader stations densely allocated close to each other are susceptible to reader collision problems. They are characterized by reader-to-tag and reader-to-reader interferences. Both degrade the system performance, decreasing the number of tags identified per time unit. Although some proposals have been suggested to avoid/handle these collisions, most of them require extra hardware, do not make an efficient use of the network resources and are not compatible with the current standards and regulations. This paper proposes a centralized and aligned scheduler that optimizes the distribution of network resources (frequencies and time slots) among the readers in the network. Those readers with unidentified tags in their target region will have higher priority for receiving resources. The optimization problem is formulated as a Mixture Integer Programming problem. Results show that the method proposed provides higher network throughput and fairness than the EPCglobal Class-1 Gen-2 standard for dense reader environments. In addition, unlike previous works, the scheduling algorithm presented is compatible with EPCglobal standard and the European regulation, and can be implemented in real RFID systems with fixed and mobile readers.     

一种基于ALOHA的改进RFID防碰撞算法

标签碰撞是无线射频识别(RFID)技术中的常见问题,它使得系统效率降低。ALOHA算法是解决此类问题的重要方法,提出了一种基于ALOHA的改进防碰撞算法,并分别给出了应用该方法处理碰撞时,阅读器和标签各自需要执行的程序步骤。仿真结果表明,该算法具有较高的效率,尤其在标签数量较大时相比动态帧时隙算法(DFSA)消耗时隙更少。