数据结构之查找实例演示系统的设计与实现

本系统是算法实例演示系统的一部分,设计的主要内容：静态查找（顺序查找、折半查找、分块查找）,动态查找（二叉排序树的查找、二叉平衡树的查找）以及基于哈希表的查找（开放地址法、再哈希法、链地址法）。通过实例形象地把查找过程给演示出来,突出教与学的交互性。系统在教学中得到实践检验,效果较好。     

基于平衡二叉树和Bloom过滤器的可变长地址路由查找算法

可变长地址是未来网络领域的重要研究内容之一。针对传统路由查找算法在面向可变长地址时查找效率低的问题，提出一种基于平衡二叉树AVL(Adelson-Velskii and Landis)树和Bloom过滤器的适用于可变长地址的高效路由查找算法，简称为AVL-Bloom算法。首先，针对可变长地址灵活可变且无界的特点，利用多个片外哈希表分别存储前缀比特位数相同的路由条目及其下一跳信息，同时应用片上Bloom过滤器加速搜索可能匹配的路由前缀；其次，为了解决基于哈希技术的路由查找算法在查找最长前缀路由时需多次哈希对比的问题，引入AVL树技术，即通过AVL树组织每组路由前缀集合的Bloom过滤器及其哈希表，优化路由前缀长度的查询顺序，并减少哈希计算次数进而降低查询时间；最后，在3种不同的可变长地址数据集上将所提算法与METrie(Multi-Entrance-Trie)和COBF(Controlled prefix and One-hashing Bloom Filter)这两种传统路由查找算法进行对比实验。实验结果表明，AVL-Bloom算法的查询时间明显少于METrie和COBF算法，分别减少...     

基于哈希树的度量证据可信存储方案设计

计算平台的可信性由远程证明过程中提供的度量证据进行验证,验证程序根据计算平台在启动过程创建的度量证据建立信任。度量值扩展操作创建的度量证据和相关度量记录是线性的,查找效率较低。提出一种基于平衡二叉哈希树的构建度量证据的方法。计算平台上组件的度量值作为树叶,所有组件的度量值集合的度量值作为树根。在验证计算平台的过程中,使用哈希树的度量记录和根寄存器,在度量证据与标准值比较时显著提高错误组件查找的速度,从而提高效率。实验结果表明,平衡二叉哈希树模型在不增加空间复杂度的同时,查询时间开销显著减少。     

使用Hash表和树位图的两级IPv6地址查找算法

为了提高IPv6地址查找效率,在分析IPv6路由前缀长度分布规律的基础上,提出了基于哈希表及树位图(Tree-bitmap)的两级IPv6地址查找算法.算法将长度为16,32,48和64比特的前缀分别存储在4个Hash表中,其余前缀的前16,32和48比特利用已有的Hash表存储,剩余的不足16比特的部分前缀利用树位图存储,并将树位图的入口地址保存在Hash表中.IP地址查找时在Hash表和树位图中进行两级查找.实验表明,该查找算法的平均内存访问次数为1～2,最坏情况下为7,适用于高速IPv6地址查找.     

基于无冲突哈希表和多比特树的两级IPv6路由查找算法

为了提高IPv6的路由查找效率,根据IPv6路由前缀分布规律和前缀层次关系,提出了基于无冲突哈希表和多比特树的两级IPv6路由查找算法。该算法将地址前缀划分区间并按长度为32,40,48比特分别存储于3个哈希表中,剩下不足的前缀比特由多比特树存储,IPv6路由查找时在无冲突哈希表和多比特树中两级查找。实验表明,该查找算法的平均查找路径数为1.0~1.7,适用于高速的IPv6路由查找。     

二叉排序树查找算法性能分析

查找是计算机中经常要用到的操作。二叉排序树排序树查找属于动态查找类,二叉排序树查找算法与建立算法密切相关。给出了一种计算二叉排序树平均查找长度的算法,希望能对查找算法的研究起到一点作用。     

一种哈希表快速查找的改进方法

哈希表由于其速度快的优点在数据查询中有着广泛的应用。本文在结合冲突解决机制和数据元素被查找的先验概率的基础上,提出了一种提高哈希表查找效率的优化方法,并对该方法在链地址法处理哈希冲突的情况下进行了理论分析,与原哈希表方法相比,该方法降低了冲突时执行查询的查找长度,从而使查询响应时间更短。最后对该方法进行行了实例验证,实验结果表明,新方法是有效并且简便的。     

基于查找树的IP地址分类算法研究

随着Internet的大规模发展,越来越多的网络业务需要对IP地址进行适时、快速分类.在分析二叉Trie树的基础上,改进了其结构,提出了基于256-叉查找树的IP地址分类算法,并详细介绍了其实现过程,比较了它们的优缺点.该算法在满足空间要求的情况下,提高了查找分类时间,具有通用性和实用价值.     

动态规划法构建最优二叉查找树的研究

提出动态规划法构建最优二叉查找树的算法模型,并对其进行改进,构造实例表明算法的有效性。     

哈希表查找算法的性能分析与研究

查找是计算机中经常要用到的操作.哈希查找试图不通过关键字的比较就可以确定元素记录所在的地址,极大地减少了关键字的比较次数,提高了查找的性能.给出了一种通过链地址法处理冲突构造的哈希表,并计算平均查找长度的算法,希望能对查找算法的研究起到一点作用.     

An efficient IP address lookup algorithm based on a small balanced tree using entry reduction

Due to a tremendous increase in internet traffic, backbone routers must have the capability to forward massive incoming packets at several gigabits per second. IP address lookup is one of the most challenging tasks for high-speed packet forwarding. Some high-end routers have been implemented with hardware parallelism using ternary content addressable memory (TCAM). However, TCAM is much more expensive in terms of circuit complexity as well as power consumption. Therefore, efficient algorithmic solutions are essentially required to be implemented using network processors as low cost solutions.Among the state-of-the-art algorithms for IP address lookup, a binary search based on a balanced tree is effective in providing a low-cost solution. In order to construct a balanced search tree, the prefixes with the nesting relationship should be converted into completely disjointed prefixes. A leaf-pushing technique is very useful to eliminate the nesting relationship among prefixes [V. Srinivasan, G. Varghese, Fast address lookups using controlled prefix expansion, ACM Transactions on Computer Systems 17 (1) (1999) 1-40]. However, it creates duplicate prefixes, thus expanding the search tree.This paper proposes an efficient IP address lookup algorithm based on a small balanced tree using entry reduction. The leaf-pushing technique is used for creating the completely disjointed entries. In the leaf-pushed prefixes, there are numerous pairs of adjacent prefixes with similarities in prefix strings and output ports. The number of entries can be significantly reduced by the use of a new entry reduction method which merges pairs with these similar prefixes. After sorting the reduced disjointed entries, a small balanced tree is constructed with a very small node size. Based on this small balanced tree, a native binary search can be effectively used in address lookup issue. In addition, we propose a new multi-way search algorithm to improve a binary search for IPv4 address lookup. As a result, the proposed algorithms offer excellent lookup performance along with reduced memory requirements. Besides, these provide good scalability for large amounts of routing data and for the address migration toward IPv6. Using both various IPv4 and IPv6 routing data, the performance evaluation results demonstrate that the proposed algorithms have better performance in terms of lookup speed, memory requirement and scalability for the growth of entries and IPv6, as compared with other algorithms based on a binary search.     

基于FAQ的智能答疑系统中分词模块的设计

在基于FAQ的智能答疑系统中,分词处理是基础和关键。分词质量的好坏直接影响智能答疑系统的准确性。针对实际应用领域的需要,本系统分词模块采取普通词典和专业词典混合的词典设计方案,分词算法采用正向最大匹配的分词算法。为了提高词典的查找速度,分词词典采用Hash表和二维数组的数据结构,根据汉字的内码利用Hash方法,求得在内存的地址,然后计算其索引项的二维数组的下标,对于词典的搜索采用二分查找法。实验结果表明：该分词系统提高了智能答疑系统的效率和准确率。     

二进制一维矩阵搜索防碰撞算法

针对典型二进制搜索算法存在的搜索次数多、数据传输量大、系统识别效率低的问题,提出了一种二进制一维矩阵搜索防碰撞改进算法。该算法根据检测到的标签碰撞位信息构造二进制搜索矩阵,并确定相应的碰撞位对应值矩阵对标签进行搜索,通过对搜索前缀进行改进,使得读写器与标签之间传输量减少,且在标签识别过程中,碰撞位矩阵及其对应值矩阵需根据碰撞位的改变进行修改,以实现读写器对标签的连续搜索及识别。实例说明及Matlab仿真结果表明,随着标签数目的增加,改进算法的搜索次数和总的数据传输量增加相对较少,系统吞吐率提高,可达66%~78%,系统的识别过程加快。     

基于栈的恶意程序隐式系统调用的检测方法

提出了一种检测恶意程序中隐式系统调用的方法.该方法使用地址栈和地址栈图来检测恶意程序中隐式的系统调用信息,其中,地址栈将每个栈的元素和栈操作的指令相结合,而地址栈图抽象地表示可执行体并且检测恶意的系统调用.通过实验表明,这是一种有效的方法.     

射频识别系统中的防碰撞算法研究

在RFID系统中,为解决多个标签同时与阅读器交换数据所引起的碰撞问题,必须采用一定的防碰撞算法,标签防碰撞技术是RFID系统中的关键技术。详细分析了典型的二进制及动态二进制防碰撞算法原理,并在此基础上提出了一种新的防碰撞算法。该算法根据标签碰撞的特点,充分利用已得到的冲突信息,采用休眠计数的方法,使搜索范围大大缩小,提高了标签的识别效率。性能分析表明,该算法比已有的二进制及动态二进制反碰撞算法具有更明显的优势。     

Binary search networks: A new method for key searching

A novel method for key searching, binary search networks, is proposed, and its search, insertion, and deletion algorithms are presented. A binary search network is an extension of a binary search tree which is widely used as a practical key search method.Some properties of binary search networks are discussed, and the optimization problem of minimizing a search cost is remarked upon. The advantages and disadvantages of binary search networks relative to binary search trees are also discussed.     

Ant Colony Optimization based approach for efficient packet filtering in firewall

A firewall is a security guard placed at the point of entry between a private network and the outside network. The function of a firewall is to accept or discard the incoming packets passing through it based on the rules in a ruleset. Approaches employing Neural networks for packet filtering in firewall and packet classification using 2D filters have been proposed in the literature. These approaches suffer from the drawbacks of acceptance of packets from the IP address or ports not specified in the firewall rule set and a restricted search in the face of multiple occurrences of the same IP address or ports respectively. In this paper we propose an Ant Colony Optimization (ACO) based approach for packet filtering in the firewall rule set. Termed Ant Colony Optimization Packet Filtering algorithm (ACO-PF), the scheme unlike its predecessors, considers all multiple occurrences of the same IP address or ports in the firewall rule set during its search process. The other parameters of the rule matching with the compared IP address or ports in the firewall ruleset are retrieved and the firewall decides whether the packet has to be accepted or rejected. Also this scheme has a search space lesser than that of binary search in a worst case scenario. It also strictly filters the packets according to the filter rules in the firewall rule set. It is shown that ACO-PF performs well when compared to other existing packet filtering methods. Experimental results comparing the performance of the ACO-PF scheme with the binary search scheme, sequential search scheme and neural network based approaches are presented.     

VOIP系统中地址映射表的创建

基于树形的存储结构及其查询方法 ,提出了适用于 VOIP系统的地址映射表创建方法 ,设计了地址映射表的数据类型与存储结构。实验表明 :采用树形存储结构构成的地址映射表 ,大大地减少了查询的耗费时间。     

Relative similarity preserving bitwise weights generated by an adaptive mechanism

Due to its high query speed and low storage cost, binary hashing has been widely used in approximate nearest neighbors (ANN) search. However, the binary bits are generally considered to be equal, which causes data points with different codes to share the same Hamming distance to the query sample. To solve the above distance measure ambiguity, bitwise weights methods were proposed. Unfortunately, in most of the existing methods, the bitwise weights and the binary codes are learnt separately in two stages, and their performances cannot be further improved. In this paper, to effectively address the above issues, we propose an adaptive mechanism that jointly generate the bitwise weights and the binary codes by preserving different types of similarity relationship. As a result, the binary codes are utilized to obtain the initial retrieval results, and they are further re-ranked by the weighted Hamming distance. This ANN search mechanism is termed AR-Rank in this paper. First, this joint mechanism allows the bitwise weights and the binary codes to be used as mutual feedback during the training stage, and they are well adapted to one other when the algorithm converges. Furthermore, the bitwise weights are required to preserve the relative similarity which is consistent with the nature of ANN search task. Thus, the data points can be accurately re-sorted based on the weighted Hamming distances. Evaluations on three datasets demonstrate that the proposed AR-Rank retrieval system outperforms nine state-of-the-art methods.