计算网络两终端可靠度的新分解算法

网络可靠度是衡量网络性能的一个核心指标,随着网络模型被广泛应用于现实生活,人们对网络可靠度的研究也越来越重视。针对不交和算法和因子分解算法在计算网络可靠度方面存在的不足,给出一个计算网络两终端可靠度的新分解算法。该算法具有如下的优点：不需要提前枚举网络的所有极小路和所有极小割;通过引入网络化简操作和新的分解技术。该算法每次可以分解多条边的状态,从而它能够更快速、更高效地去分解网络的状态向量集,使得网络可靠度的计算更简单,更高效。通过实例以及和其他算法的比较验证了所提出算法的正确性和有效性。     

因子定理的矩阵表示及网络两终端可靠度的计算

提出了网络的 s- t概率矩阵及其可靠度的概念 ,给出了矩阵的一个变换和几个保持可靠度不变的矩阵的化简原则以及因子定理的矩阵表示 ,从而建立了一个计算网络两终端可靠度 (s- t可靠度 )的迅速而有效的算法 ,并且通过上机实验验证了算法的有效性     

因子定理的矩阵表示及网络终端可靠度的计算

提出了网络的s-t概率矩阵及其可靠度的概念，给出了矩阵的一个变换和几个保持可靠度不变的矩阵的化简原则以及因子定理的矩阵表示，从而建立了一个计算网络两终端可靠度（s-t可靠度）的迅速而有效的算法，并且通过上机实验验证了算法的有效性。     

不交和公式及其在网络可靠度计算中的应用

提出了不交和公式及其在网络可靠度计算中的应用,和传统的算法相比,该算法操作简便,易于实现,计算复杂度小的点,从而适合于大型网络可靠度的计算。     

基于网络化简和向量集分解的网络两终端可靠度算法*

可靠度是衡量网络性能最重要的指标之一,不交和算法和因子分解算法是计算网络可靠度最重要的两种方法。不交和算法需要提前枚举网络所有极小路或极小割,因子分解算法虽然不需要枚举极小路或极小割,但每次只能分解一条边的状态。为了克服这两种算法的不足,基于网络化简和向量集分解,提出一个计算网络可靠度的高效、实用算法。该算法具有如下特点：a）算法首先求得网络的不可靠度,进而可得网络的可靠度;b）算法不需要提前枚举网络所有极小路和极小割;c）通过引入网络化简操作和向量集分解方法,算法每次可以分解多条边的状态,从而能更快速、     

基于遗传算法的计算机网络可靠度优化计算

在提高计算机网络传输系统可靠度的基础上,如何有效的降低网络结点链路成本,成为计算机网络可靠度优化计算中的重要目标之一。为此,在计算机网络可靠度优化计算时,将计算机网络链路介质成本、网络可靠度优化的数学模型等因素综合在一起进行考虑,文章阐述了遗传算法及其执行过程,并对遗传算法用于网络链路成本和网络可靠度优化的计算中,最后通过仿真结果表明,遗传算法能够有效的解决网络传统算法难以解决的可靠度优化计算问题,加快了计算机网络计算的速度,优化了网络的计算效果。     

基于边状态枚举计算多状态网络可靠度动态界

为降低计算多状态网络可靠度的复杂性,综合考虑网络中具有多态性的边处于各中间状态的概率及从某中间状态转换到相邻状态对网络性能的影响,提出了一种基于边状态枚举计算多状态网络可靠度上下界的算法.该算法首先令网络中各边仅取完全工作和完全失效两种状态,将处于中间状态的概率分别叠加到完全工作和完全失效状态的概率上,得到可靠度上下界的初始值;而后按照对可靠度影响递减的顺序迭代枚举边的中间状态,通过集合间的比较,计算可靠度上下界的改变值,同时获得不断减小的可靠度上界和不断增加的可靠度下界,使其最终收敛于可靠度精确值.该算法不需提前求取网络d-最小割(路)集,且枚举较少的网络状态即可得到紧凑的可靠度上下界.相关引理的证明及算例分析验证了该算法的正确性和有效性.     

因子分解二终端网络可靠度近似计算

因子分解算法可以用来计算网络可靠度精确值,但对于大型网络,可靠度精确值的计算非常困难。基于时间和精确度的双重考虑,在精确算法的基础上通过改进得出一种近似算法。实验结果证明,该算法得到的近似值接近精确值,而且计算时间要低于精确算法。     

计算节点不可靠网络可靠度的一种MDD算法

节点或边不可靠网络的可靠度分析问题是NP-hard问题,网络节点和边都不可靠的假设更接近现实。基于网络节点和边二元状态的假设,构建了节点和边不可靠网络的形式化模型,给出了分析节点和边不可靠网络可靠度的NEF_MDD算法。该算法将单个节点与其未访问邻接边划分为一个集合,通过枚举节点和边的不同组合,合并导致子网同构的冗余状态,获得简化后的状态向量和可靠度向量,并用一个多值决策图变量来表述。通过使用自定义的MDD操作算子,构建整个网络的MDD,遍历MDD节点,计算网络的可靠度。与二元决策图方法相比,该方法能够降低决策图层数和节点规模,有助于节点和边不可靠网络的可靠度分析。     

用改进的OBDD方法计算通信网可靠度*

提出一种改进的OBDD（ordered binary decision diagram）方法来计算通信网可靠度。该方法考虑了网络共因失效带来的部件故障,使得计算更加准确。在创建原始网络的OBDD结构后,根据共因变量集来计算网络可靠度。由于只创建并保存一个OBDD结构,可节省大量的计算时间和存储空间。实验证明,该方法能有效计算网络可靠度,其计算时间和存储空间要低于一般的OBDD方法。     

Optimal resource assignment to maximize multistate network reliability for a computer network

Computer network is a major tool to transmit data in our modern society. How to evaluate and enhance network reliability is thus an important issue for organizations, especially to maximize network reliability. A computer network is a multistate network in which each edge has several possible capacities with a probability distribution and may fail. The multistate network reliability is the probability that the maximal flow is no less than a given demand. From the standpoint of quality management, a further problem is to reassign the existing resources for maximizing multistate network reliability without changing the network topology. Hence, this paper focuses on the resource assignment problem to propose an efficient approach based on the simple genetic algorithm. In which, a resource assignment is represented as a chromosome and the corresponding multistate network reliability is the fitness value of the chromosome. The experimental results show that the proposed algorithm can derive the optimal resource assignment in a reasonable time.     

通信网络可靠性评估的一种算法

本文分别对等故障率和不等故障率链路所组成的通信网的可靠性进行分析,提出相应的评估算法,并用实例说明算法执行过程。1、对等故障率链路所组成的通讯网,依据图论统计含网络图所有顶点的支撑子图的数目,然后给出通信网可靠性的估算公式。2、对不等故障率链路组成的通讯网,首先给出生成网络图的所有支撑树的算法,并把其定义为成功函数,利用排它算子,给出评估通信网可靠性的算法。     

Measure the quality level for a supplier-demand system by a multicommodity stochastic-flow network

From the point of view of quality management, it is important to meet the customer's demand. The probability that the system can satisfy the customer's demand is an important performance index, and can be used to measure the quality level of the system. In this paper, we use a multicommodity stochastic-flow network to describe the relationship between the supplier and the customer. Each node as well as each arc has several possible capacities and may fail. The network allows multiple types of commodities to be transmitted from the source to the sink. Given the demand for each commodity at the sink, evaluation of the probability that the system meets the demands is performed. Such a probability, named the system reliability, is a performance index of quality level. At first, a simple algorithm is proposed to generate all lower boundary points for the demand, and the system reliability can be calculated in terms of such points. The computational complexity of the proposed algorithm is polynomial time in number of arcs, nodes and minimal paths.     

Using minimal cuts to optimize network reliability for a stochastic computer network subject to assignment budget

In our modern society, information and data are usually transmitted through a computer network. Since the computer network's reliability has a great impact on the quality of data transmission, many organizations devote to evaluating or improving network reliability, especially for network reliability optimization. This study focuses on such a confronted problem that is to find the optimal transmission line assignment to the computer network such that network reliability is maximized subject to the budget constraint. Each transmission line owns several states due to failure, maintenance, etc., and thus the computer network associated with any transmission line assignment is called a stochastic computer network. Network reliability is the probability that the computer network can transmit the specified units of data successfully. Because the discussed problem is NP-hard, an optimization algorithm that integrates the genetic algorithm, minimal cuts and Recursive Sum of Disjoint Products is proposed. Experimental results illustrate the solution procedure and show that the proposed algorithm can be executed in a reasonable time.     

基于可靠连通支配集的高效虚拟骨干网构建算法

在概率性无线传感器网络模型中,提出了一种基于可靠连通支配集的高效虚拟骨干网构建算法(EVBP-RCDS).在删除网络中低于节点递交概率阈值的连接基础上,通过递减节点递交概率和对比节点递交概率有效度(EDDP)之和构建出所提出的可靠连通支配集;非支配节点选取与其相邻的拥有最高递交概率的支配节点传输数据.仿真实验表明:与现有文献中的两种算法相比,EVBP-RCDS算法能高效扩展网络生存时间和降低网络延迟.     

Extend the quickest path problem to the system reliability evaluation for a stochastic-flow network

From the point of view of quality management, it is an important issue to reduce the transmission time in the network. The quickest path problem is to find the path in the network to send a given amount of data from the source to the sink such that the transmission time is minimized. Traditionally, this problem assumed that the capacity of each arc in the network is deterministic. However, the capacity of each arc is stochastic due to failure, maintenance, etc. in many real-life networks. This paper proposes a simple algorithm to evaluate the probability that d units of data can be sent from the source to the sink through the stochastic-flow network within T units of time. Such a probability is called the system reliability. The proposed algorithm firstly generates all lower boundary points for (d,T) and the system reliability can then be computed in terms of such points.Scope and purposeThe shortest path problem is a well-known problem in operations research, computer science, etc. Chen and Chin have proposed a variant of the shortest path problem, termed the quickest path problem. It is to find a path in the network to send a given amount of data from the source to the sink with minimum transmission time. More specifically, the capacity of each arc in the network is assumed to be deterministic. However, in many real-life networks such as computer systems, telecommunication systems, etc., the capacity of each arc is stochastic due to failure, maintenance, etc. Such a network is named a stochastic-flow network. Hence, the minimum transmission time is not a fixed number. This paper proposes a simple algorithm to evaluate the probability that the specified amount of data can be sent from the source to the sink through the network within a given time. Such a probability is called the system reliability.     

Computer network reliability optimization under double-resource assignments subject to a transmission budget

This paper discusses a double-resource assignment problem to maximize network reliability for a computer network. The resources are separated into two types: one is transmission line and another is transmission facility. In particular, each resource is multistate due to full failure, partial failure, or maintenance. Such a network assigned with multistate resources is usually modeled as a stochastic-flow network. Furthermore, each resource should have a transmission cost in reality. Hence, the network reliability is the probability that a specified demand is transmitted through the network successfully subject to a transmission budget. This paper devotes to find out the optimal double-resource assignment with maximal network reliability. An optimization algorithm combining the genetic algorithm, the minimal paths, and the Recursive Sum of Disjoint Products is developed to solve the proposed problem. The experimental results show that the proposed algorithm can be executed in a reasonable time.     

异构无线网络中基于非合作博弈论的资源分配和接入控制

对异构无线网络中无线资源分配和呼叫接入控制进行研究.基于非合作博弈理论,提出了不同无线资源的带宽和连接数量分配的理论模型.结合网络连接的效用函数,对非合作博弈的无线资源分配中的纳什均衡点的存在性和唯一性进行论证.而且,进一步对业务量与阻塞率之间的关系进行分析,提出了能够保证通信可靠性的接入控制算法.仿真结果表明,基于非合作博弈论的无线资源分配机制能够有效地解决带宽和连接数量的分配问题,并能在整体上保证分配的合理性和公平性.接入控制算法根据需要能够动态地调整在某一区域分配的连接数量,从而保证通信的可靠性.