新颖的无线传感器网络组网算法

为有效解决无线传感器网络的网络维护困难性问题,研究性能更好的网络组网算法是一种有效的解决手段．本文给出了无线传感器网络体系结构模型及其连通性定义,在此基础上本文提出了一个具有网络连通性能好的无线传感器网络组网算法并进行了仿真分析,由该算法构成的无线传感器网络不仅具有连通性能好,而且具有保护网络节点能量和控制网络功率的优良特点,所以在传感器网络实际应用中有着光明的前景．     

动态社会网络中的社区演变挖掘

在静态网络图中对社会网络进行分析,可能忽略网络的时间特性,从而错过捕捉动态网络演变模式的机会.为检测社区的演变及社区结构随时间的变化,分析动态社区,为每一个社区定义一系列重大事件,给出社区匹配算法,并对元社区的概念进行定义.实验结果证明,采用该算法建模和检测社会网络中的社区演变,可有效识别和追踪随时间变化的相似社区.     

基于图的语义网络构造算法研究

在自然语言处理的基础上,将中医领域本体与图的基本性质相结合,提出了构造中医诊疗知识语义网络算法.给出了图的基本性质、语义网络的图定义,并为知识的网络表示建立了相应的数据结构.将算法用于中医领域语义网络和语义场构建.试验结果表明,该算法具有较好的实用性.提出的基于图的语义网络构造算法,对于文本挖掘、知识获取技术研究有重要意义,也是中医专家知识获取的有效方法.     

基于Amorphous的无线传感器网络定位算法研究

简述Amorphous算法的定义及应用,详细的给出了Amorphous定位算法的步骤,系统分析了影响Amorphous算法定位精度的参数,包括锚节点的个数、节点通信半径和总节点的数目.给出了仿真结果并通过对仿真结果分析得出了上述参数的较优值.仿真结果表明,使用这些优化的参数,Amorphous算法可以有效降低无线传感器网络的节点的定位误差.     

基于图的语义网络构造算法研究

在自然语言处理的基础上,将中医领域本体与图的基本性质相结合,提出了构造中医诊疗知识语义网络算法。给出了图的基本性质、语义网络的图定义,并为知识的网络表示建立了相应的数据结构。将算法用于中医领域语义网络和语义场构建。试验结果表明,该算法具有较好的实用性。提出的基于图的语义网络构造算法,对于文本挖掘、知识获取技术研究有重要意义,也是中医专家知识获取的有效方法。     

分层抽样的无标度复杂网络可靠性度量算法

针对大型无标度复杂网络的幂律分布特性,提出了一种基于分层抽样技术的算法SSBA,通过分析样本网络推导出大型无标度复杂网络的可靠性度量参数,并给出这些参数的Bootstrap置信区间。大量的实验表明,SSBA算法能有效估算出大型无标度复杂网络的可靠性度量参数。     

基于脆弱性关联模型的网络威胁分析

为了解决网络脆弱性建模存在的问题以及威胁评估方法中的不足,结合面向对象技术提出了基于扩展时间Petri网的脆弱性关联模型,通过定义攻击复杂度和危害度因素以及各评估指标的量化方法,给出了脆弱性关联模型的生成算法。结合网络威胁度的计算公式,运用改进的Dijkstra算法给出了无目标导向的网络威胁量化分析方法。该模型能够有效缩减状态空间的规模,适合对复杂网络攻击建模。实验证明了脆弱性关联模型的正确性及其优越的描述性能,基于该模型的威胁分析方法也更为合理、有效。     

基于HTK的语音识别网络优化算法

隐马尔可夫模型工具包(HTK)的HParse命令根据用户以正则表达式形式定义的任务语法来生成HTK可用的底层表示的语音识别网络,但不是每个语句都能用正则表达式表示出来。针对该问题,提出基于HTK的语音识别网络算法用于识别网络的优化问题,给出该算法的具体实现过程。实验结果表明,在保证识别率的前提下,优化后的语音识别网络在语音识别系统中所用的时间比较短,算法是有效的。     

基于模糊结构元的最小生成树问题的求解算法

针对梯形模糊数,定义了一种梯形模糊结构元.研究了边权值为梯形模糊数的模糊权值网络,建立了其最小生成树问题的数学模型,并利用梯形模糊结构元加权排序思想和Kruskal算法,设计了一种该问题的求解算法,给出了算法的复杂度分析和应用实例.文中的模型和算法对于边权值为其他类型模糊数的模糊权值网络同样有效.     

基于层次扩展SPN的网络攻击模型

当前网络攻击模型对于复杂系统的建模能力较差。为此,提出一种基于层次扩展随机Petri网的全网攻击模型。该模型对宏观网络攻击和微观主机攻击具有较好的综合描述能力,适用于网络协同式组合攻击行为的模拟,并能够有效解决网络状态空间爆炸问题。基于该模型,提出一种生成算法,通过对网络粗糙攻击路径的定义,给出挖掘主机结点间潜在的攻击关系算法。经过子网扩展后,利用蚁群算法找出k条最优攻击路径,通过对粗糙攻击路径和精确攻击路径的综合评价,给出网络危险性定量评估方法。     

A tool for computing computer network reliability

The computation of the reliability of a computer network is one of the important tasks of evaluating its performance. The idea of minimal paths can be used to determine the network reliability. This paper presents an algorithm for finding the minimal paths of a given network in terms of its links. Then, it presents an algorithm for calculating the reliability of the network in terms of the probabilities of success of the links of its minimal paths. The algorithm is based on a relation that uses the probabilities of the unions of the minimal paths of the network to obtain the network reliability. Also, the paper describes a tool that has been built for calculating the reliability of a given network. The tool has two main phases: the minimal paths generation phase, and the reliability computation phase. The first phase accepts the links of the network and their probabilities, then implements the first proposed algorithm to determine its minimal paths. The second phase implements the second proposed algorithm to calculate the network reliability. The results of using the tool to calculate the reliability of an example network are given.     

System reliability maximization for a computer network by finding the optimal two-class allocation subject to budget

In the real world, a computer/communication system is usually modeled as a capacitated-flow network since each transmission line (resp. facility) denoted by an edge (resp. node) has multiple capacities. System reliability is thus defined to be a probability that d units of data are transmitted successfully from a source node to a sink node. From the perspective of quality management, system reliability is a critical performance indicator of the computer network. This paper focuses on maximizing system reliability for the computer network by finding the optimal two-class allocation subject to a budget, in which the two-class allocation is to allocate exactly one transmission line (resp. facility) to each edge (resp. node). In addition, allocating transmission lines and facilities to the computer network involves an allocation cost where the cost for allocating a transmission line depends on its length. For solving the addressed problem, a genetic algorithm based method is proposed, in which system reliability is evaluated in terms of minimal paths and state-space decomposition. Several experimental results demonstrate that the proposed algorithm can be executed in a reasonable time and has better computational efficiency than several popular soft computing algorithms.     

Backup reliability of stochastic imperfect-node computer networks subject to packet accuracy rate and time constraints

In a real-time computer network, arcs and nodes have multi-state capacity, lead time, and packet accuracy rate (PAR). Evaluating the reliability of a network whose nodes are imperfect is complex, because node failure results in the disablement of adjacent arcs. Such a network is named a stochastic imperfect-node computer network (SINCN). Under the strict assumption that each arc has a deterministic capacity, the quickest path problem is to find a path that sends a specific amount of data with minimum transmission time. Subject to both an assured PAR and time constraints, this paper proposes an efficient algorithm to evaluate the system reliability of an SINCN. Furthermore, a routing scheme is adopted to reinforce the system reliability. Accordingly, reliability based on the routing scheme is calculated. An application of our method on the Taiwan academic network is described to show its impact on the backup reliability for different routing schemes.     

覆盖模型的传感器网络寿命问题建模及其求解

针对传感器网络的寿命问题(SNLP),提出了一种传感器网络覆盖模型及其数据结构,并把该问题等效为它的对偶问题——最小权值传感器覆盖问题.首先,把SNLP构建为一个包装线性规划,在找到满足传感器网络约束的不同传感器覆盖后,通过为每个传感器覆盖分配时间来使传感器网络寿命最大化;其次,对于求解SNLP,提出了基于Garg-K...     

证券行情广播系统的研究与实现

对以软件为主的证券行情传输解决方案进行了分析，在现行证券行情传输软件系统的基础上采用了一种新型的行情编码解码算法和数据传输机制，极大地提高了软件的效率和适应性，并对压缩解压算法的应用和实现以及网络数据传输的可靠性和效率改进作了一些探讨。     

Transient chaotic neural network-based disjoint multipath routing for mobile ad-hoc networks

Due to mobility of wireless hosts, routing in mobile ad-hoc networks (MANETs) is a challenging task. Multipath routing is employed to provide reliable communication, load balancing, and improving quality of service of MANETs. Multiple paths are selected to be node-disjoint or link-disjoint to improve transmission reliability. However, selecting an optimal disjoint multipath set is an NP-complete problem. Neural networks are powerful tools for a wide variety of combinatorial optimization problems. In this study, a transient chaotic neural network (TCNN) is presented as multipath routing algorithm in MANETs. Each node in the network can be equipped with a neural network, and all the network nodes can be trained and used to obtain optimal or sub-optimal high reliable disjoint paths. This algorithm can find both node-disjoint and link-disjoint paths with no extra overhead. The simulation results show that the proposed method can find the high reliable disjoint path set in MANETs. In this paper, the performance of the proposed algorithm is compared to the shortest path algorithm, disjoint path set selection protocol algorithm, and Hopfield neural network (HNN)-based model. Experimental results show that the disjoint path set reliability of the proposed algorithm is up to 4.5 times more than the shortest path reliability. Also, the proposed algorithm has better performance in both reliability and the number of paths and shows up to 56% improvement in path set reliability and up to 20% improvement in the number of paths in the path set. The proposed TCNN-based algorithm also selects more reliable paths as compared to HNN-based algorithm in less number of iterations.     

网络系统可靠度的连接矩阵逻辑扩展算法

针对网络性能优化技术,着重研究无线网络传输可靠性问题,为有效提高3-状态无圈有向设备网络系统二终端可靠度仿真算法效率;采用网络的连接矩阵表示形式,在定义了连接矩阵列变换后,依据连接矩阵逻辑扩展技术对连接矩阵实施连续的代数变换,得到了求3-状态设备网络二终端可靠度的一个有效快速算法。仿真示例表明,使网络系统可靠度符号表达式中项数大幅度减少,算法效率显著提高。由于算法使用了网络系统的代数化表示方法,结合了消除冗余项存储及简化技术,算法具有节约存储空间、执行效率高特点。对复杂网络系统可靠度评估具有重要参考价值。     

网络系统的可靠性预计新方法

首先给出了一种将混合网络转变为单向网络的方法,提出了一种新的最小割集求解算法,在节约内存空间的同时,方便了每个节点的遍历,简化了编程计算步骤。然后给出了网络可靠性计算的ESP算法及其改进的线性逼近算法。最后用某复杂系统任务可靠性预计结果分析验证了论文算法的正确性和有效性。     

An anticipation mechanism for the shortest path problem based on Physarum polycephalum

In this paper, we put forward an anticipation mechanism for the existing Physarum-inspired shortest path finding method. The Physarum-based shortest path finding model can be implemented by an iterative algorithm and has wide applications in many fundamental network optimization problems. In this paper, we mainly focus on the Physarum-inspired shortest path tree model. Normally, we stop the program when the difference between two consecutive iterations is less than a predefined threshold. However, we do not know how to set the specific value for the threshold variable. In order to find out the optimal solution, we need to set the threshold as a very small number. This in turn will consume a lot of time. From this point of view, this algorithm lacks an efficient and reliable mechanism to judge when the optimal solution will be found. In this paper, we introduce an anticipation mechanism to address this issue. Numerical examples are used to demonstrate its reliability and efficiency.