A stochastic node-failure network with individual tolerable error rate at multiple sinks

Many enterprises consider several criteria during data transmission such as availability, delay, loss, and out-of-order packets from the service level agreements (SLAs) point of view. Hence internet service providers and customers are gradually focusing on tolerable error rate in transmission process. The internet service provider should provide the specific demand and keep a certain transmission error rate by their SLAs to each customer. This paper is mainly to evaluate the system reliability that the demand can be fulfilled under the tolerable error rate at all sinks by addressing a stochastic node-failure network (SNFN), in which each component (edge or node) has several capacities and a transmission error rate. An efficient algorithm is first proposed to generate all lower boundary points, the minimal capacity vectors satisfying demand and tolerable error rate for all sinks. Then the system reliability can be computed in terms of such points by applying recursive sum of disjoint products. A benchmark network and a practical network in the United States are demonstrated to illustrate the utility of the proposed algorithm. The computational complexity of the proposed algorithm is also analyzed.     

Stochastic computer network with multiple terminals under total accuracy rate

From the viewpoint of service level agreements,data transmission accuracy is one of the critical performances for assessing Internet by service providers and enterprise customers.The stochastic computer network(SCN),in which each edge has several capacities and the accuracy rate,has multiple terminals.This paper is aimed mainly to evaluate the system reliability for an SCN,where system reliability is the probability that the demand can be fulfilled under the total accuracy rate.A minimal capacity vector allows the system to transmit demand to each terminal under the total accuracy rate.This study proposes an efficient algorithm to find all minimal capacity vectors by minimal paths.The system reliability can then be computed in terms of all minimal capacity vectors by the recursive sum of disjoint products(RSDP) algorithm.     

基于随机移动模型的移动sinks无线移动传感器网络性能分析与改进*

引入移动sinks节点是解决网络连通性、能耗平衡、提高网络生命周期和网络容量的有效方法。针对移动sinks节点的移动机制直接与网络性能相关,结合mWSNs体系结构,分析了基于随机移动模型的网络性能,提出了零数据包分片率的随机移动模型。理论分析与仿真结果表明,该模型能够保证数据零分片,提高了网络的时延性能和数据包传输成功率。     

Reliability assessment of a multistate freight network for perishable merchandise with multiple suppliers and buyers

This study develops a multistate freight network for single and perishable merchandise to assess the freight performance, where a node denotes a supplier, a distribution centre, or a buyer, while a logistics company providing a freight traffic service is denoted by an edge. For each logistics company, carrying capacity should be multistate since partial capacity may be reserved by some customers. The merchandise may perish or be perished during conveyance because of disadvantageous weather or collision in carrying such that the number of intact cargoes may be insufficient for the buyers. Hence, according to the perspective of supply chain management, the reliability, a probability of the network to successfully deliver the cargoes from the suppliers to the buyers subject to a budget, is proposed to be a performance index, where the suppliers and buyers are not the previous customers. An algorithm in terms of minimal paths to assess the reliability is developed. A fruit logistics case is adopted to explore the managerial implications of the reliability using sensitivity analysis.     

Reliability evaluation for a manufacturing network with multiple production lines

This paper focuses on performance evaluation of a manufacturing system with multiple production lines based on the network-analysis perspective. Due to failure, partial failure, or maintenance, the capacity of each machine is stochastic (i.e., multi-state). Hence, the manufacturing system can be constructed as a stochastic-flow network, named manufacturing network herein. This paper intends to measure the probability that the manufacturing network can satisfy customers’ orders. Such a probability is referred to as the system reliability. A graphical representation is first proposed to transform a manufacturing system into a manufacturing network. Thereafter, we decompose the manufacturing network into general processing paths and reworking paths. Three algorithms are subsequently developed for different scenarios and multiple production lines to generate the minimal capacity vectors that machines should provide to satisfy demand. The system reliability can be derived in terms of such capacity vectors afterwards.     

Reliability evaluation of a multistate network subject to time constraint under routing policy

A multistate network is a stochastic network composed of multistate arcs in which each arc has several possible capacities and may fail due to failure, maintenance, etc. The quality of a multistate network depends on how to meet the customer's requirements and how to provide the service in time. The system reliability, the probability that a given amount of data can be transmitted through a pair of minimal paths (MPs) simultaneously under the time constraint, is a proper index to evaluate the quality of a multistate network. An efficient solution procedure is first proposed to calculate it. In order to further enhance the system reliability, the network administrator decides the routing policy in advance to indicate the first and the second priority pairs of MPs. The second priority pair of MPs takes charge of the transmission duty if the first fails. The system reliability under the routing policy can be subsequently evaluated.     

含有分数阶PID控制器的随机动力系统可靠性分析

随着粘弹性材料在工程结构中的广泛应用,刻画工程结构中粘弹性材料遗传特性和长记忆性的分数阶微积分成为研究的热点,特别是具有分数阶微积分特点的PID控制器更是从理论上和应用上受到关注.本文研究高斯白噪声激励下含有分数阶PID控制器的随机结构动力系统的可靠性问题.利用慢变过程的特征以及广义积分的性质,对分数阶PID控制器在数学上进行了近似处理,之后应用能量包络随机平均法确定了可靠性函数满足的后向Kolmogorov方程以及首次穿越时间统计矩满足的广义Pontryagin方程.结果表明：在分数阶控制器中,较小的分数阶α和较大的分数阶β均可以得到较为理想的可靠性结果,并且这些均与蒙特卡洛仿真结果一致,验证了方法的有效性和正确性.     

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.     

Stochastic input-to-state stability for impulsive switched stochastic nonlinear systems with multiple jumps

In this study, we investigate the stochastic input-to-state stability (SISS) of impulsive switched stochastic nonlinear systems. In this model, the impulse jumps are component multiple maps that depend on time. Thus the model differs from traditional impulsive systems with single impulse between two adjacent switching times. We provide sufficient conditions in three cases with the SISS system by using the Lyapunov function and average impulsive interval approach. The destabilising impulses cannot destroy the SISS properties if the impulses do not occur too frequently when all the subsystems that control the continuous dynamics are SISS. In other words, the average impulsive interval satisfies a lower bound restraint. Conversely, when all subsystems that control the continuous dynamics are not SISS, impulses can contribute to stabilising the system in the SISS sense when the average impulsive interval satisfies an upper bound. Then, we investigate the SISS property of impulsive switched stochastic nonlinear systems with some subsystems that are not SISS under certain conditions such that the property remains obtained. Finally, we show three examples to demonstrate the validity of the main result.     

随机风作用下高速列车动力学参数的可靠性优化设计

建立随机风作用下高速列车动力学参数的可靠性优化设计方法．首先考虑自然风的脉动特性，采用Cooper理论和谐波叠加法模拟随车移动点的脉动风速，给出随机风作用下高速列车非定常气动载荷的计算方法．然后建立高速列车车辆系统动力学模型，计算高速列车的运行安全性，并基于可靠性理论，给出随机风作用下高速列车失效概率的计算方法．在此基础上，以高速列车动力学参数为优化设计变量，以失效概率和轮轴横向力为优化目标，采用多目标遗传算法NSGA—II进行动力学参数的自动寻优，建立随机风作用下高速列车动力学参数的可靠性优化设计模型．经可靠性优化计算，高速列车的失效概率由原始的0．4884降低为0．1406，轮轴横向力由原始的45．13kN降低为43．01kN．通过优化高速列车动力学参数可以显著改善随机风作用下高速列车的运行安全性．     

随机ADD算法的不确定网络优化研究

传统的网络优化问题通过对偶梯度下降算法来解决,虽然该算法能够以分布式方式来实现,但其收敛速度较慢.加速对偶下降算法(ADD)通过近似牛顿步长的分布式计算,提高了对偶梯度下降算法的收敛速率.但由于通信网络的不确定性,在约束不确定时,该算法的收敛性难以保证.基于此,提出了一种随机形式的ADD算法来解决该网络优化问题.理论上证明了随机ADD算法当不确定性的均方误差有界时,能以较高概率收敛于最优值的一个误差邻域;当给出更严格的不确定性的约束条件时,算法则可以较高概率收敛于最优值.实验结果表明,随机ADD算法的收敛速率比随机梯度下降算法快两个数量级.     

Levy噪声下基于自适应级联三稳随机共振的4FSK信号检测

针对Levy噪声背景下数字信号检测效率较低的问题,提出了一种基于自适应级联三稳态随机共振的4FSK信号提取新方法,并与4FSK信号传统调制解调模型作对比。模拟并比较了自适应级联三稳态随机共振系统模型和传统模型的输出信号误码率。数值仿真实验结果表明,与传统调制解调模型相比,4FSK信号在经过自适应级联三稳态随机共振系统模型解调后的输出信号误码率相较于传统调制解调模型要平均降低了4%,且时域图像更为清晰,毛刺明显减少,频谱幅值大幅提升。该实验的成功表明随机共振系统对冲击噪声中的数字信号检测有很强的应用前景。     

Approximation and application of the Musiela stochastic PDE in forward rate models

In this article, we consider the Musiela equation of forward rates, which is a hyperbolic stochastic partial differential equation. A weak formulation of the problem using the streamline upwind Petrov–Galerkin method is analysed. Error analysis of the method yields estimates for the convergence rates. Computational examples are provided that illustrate not only the discretization methods used, but the type of results relevant to bond pricing that can be obtained from the equation.     

Preview control for a class of linear stochastic systems with multiplicative noise

ABSTRACT

In this paper, the preview control problem for a class of linear continuous time stochastic systems with multiplicative noise is studied based on the augmented error system method. First, a deterministic assistant system is introduced, and the original system is translated to the assistant system. Then, the integrator is employed to ensure the output of the closed-loop system tracking the reference signal accurately. Second, the augmented error system, which includes integrator vector, control vector and reference signal, is constructed based on the system after translation. As a result, the tracking problem is transformed into the optimal control problem of the augmented error system, and the optimal control input is obtained by the dynamic programming method. This control input is regarded as the preview controller of the original system. For a linear stochastic system with multiplicative noise, the difficulty being unable to construct an augmented error system by the derivation method is solved in this paper. And, the existence and uniqueness solution of the Riccati equation corresponding to the stochastic augmented error system is discussed. The numerical simulations show that the preview controller designed in this paper is very effective.     

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。     

Reliability optimization of a complex system by the stochastic branch and bound method

An optimal redundancy problem is considered as a stochastic optimization problem. The mean lifetime of a network is maximized by the stochastic branch and bound algorithm. To obtain (stochastic) estimates of branches, use is made of stochastic tangent minorants and majorants of the objective functional, interchange relaxation (permutation of maximization and expectation operations), and multiple solution of auxiliary dynamic programming problems. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 129–141, May–June 2008.     

k元n方体的可靠性评估

并行计算机系统功能的实现很大程度上依赖于系统互连网络的性能。为了精确度量以k元n方体为底层拓扑结构的并行计算机系统的容错能力,研究了点故障模型下k元n方体中k元（n-1）方体子网络的可靠性。当k ≥ 3且为奇数时,分别在固定划分模式和灵活划分模式下对k元n方体中不同数目的k元（n-1）方体子网络保持无故障状态的平均失效时间进行了分析,并得出了这一子网络可靠性评估参数的计算公式。结果表明,当基于k为奇数的k元n方体构建的并行计算机系统指派子网络执行用户任务时,在点故障模型下灵活划分模式相比固定划分模式有着更好的容错能力。     

Fluctuations of a stochastic system under an asymptotic diffusive perturbation

A stochastic singularly perturbed system is considered. Sufficient conditions of the asymptotic normality are obtained for the dynamic system in the vicinity of its equilibrium point. To this end, a solution to the singular perturbation problem is constructed for an asymptotic representation of the generator of a Markov renewal process. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 104–109, September–October 2008.     

多杂质用水网络设计方法的改进与比较

通过引入分配因子和最小限制流量对多杂质用水网络超结构模型进行改进,使模型更简捷高效;在逐步线性规划法中引入改进的超结构模型,提供了用水过程的排序依据,可代替枚举法直接排序,提高了求解效率。通过实例比较了改进前后的两种设计方法,找出了它们之间的优势和劣势,结果表明,本文的改进策略可以快速和准确地解决多杂质用水网络设计问题。     

具有双储层结构的动态误差补偿回声状态网络

针对传统回声状态网络难以有效应对高阶非线性复杂模型问题,本文在理论分析的基础上提出了一种双储层结构的误差补偿回声状态网络,并设计了该网络的学习算法.该网络由计算层和补偿层构成,计算层主要承担拟合任务,补偿层则作为状态跟随器,实时补偿由于计算层对期望方差估计不足而导致的幅值偏差.对多阶振荡器和真实高阶非线性数据集的实验结果表明,本文所提网络结构较常规网络具有更高的稳定性和泛化性能,尤其对高阶非线性复杂模型的预测精度大幅度提升.