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.     

A hybrid ant-tabu algorithm for solving a multistate flow network reliability maximization problem

Network reliability optimization for multistate flow networks (MFN) is an important issue for many system supervisors. Network reliability maximization for an MFN by determining the optimal component assignment, where a set of multistate components are ready to be assigned to the network, is a common problem. Previous research solved this problem by developing and applying genetic algorithm. Ant colony optimization (ACO) finds a good solution quickly by utilizing the experience of the proceeding ant but sometimes falls into local optimum. Tabu search (TS) adopts a tabu list to avoid searching in the same direction, and thus it explores other possible solutions. This strategy enlarges the search space. Therefore, we propose a hybrid ant-tabu (HAT) algorithm integrating the advantages of ACO and TS to solve this problem, where network reliability is evaluated in terms of minimal paths (MPs) and Recursive Sum of Disjoint Products. Experimental (RSDP) results show that the proposed HAT has better computational efficiency than several soft computing algorithms for networks with more than six MPs or 10 arcs.     

System reliability for a multi-state manufacturing network with joint buffer stations

This paper studies system reliability for a multi-state manufacturing network with multiple production lines (MSMN-MPL) considering joint buffer station. Joint buffer stations with finite volumes are set into the MSMN-MPL to temporally store blocked outputs from upstream workstations. The usage volume of each joint buffer station is therefore affected by the capacity states of workstations. An adjustment term, defined as the probability that all buffer stations are not blocked, is proposed to analyze volume usage and corresponding probability for joint buffer stations. The system reliability with finite buffer volume is evaluated accurately in terms of the adjustment term. In particular, the relationship between system reliabilities with infinite and finite buffer volumes can be formulated by multiplying the adjustment term. A practical case of footwear manufacturing system is utilized to demonstrate system reliability evaluation with both infinite and finite buffer volumes. The suggested production policy for the case is to produce 144 and 96 products by two production lines because this policy can result a higher reliability. Moreover, experimental results show that the system reliabilities with infinite and finite buffer volume are 87.190% and 83.099%, respectively. This indicates that the assumption of infinite buffer volume overestimates the system reliability in the footwear manufacturing system.     

System capacity for a two-commodity multistate flow network with unreliable nodes and capacity weight

The system capacity of a single-commodity flow network is the maximum flow from the source to the destination. This paper discusses the system capacity problem for a two-commodity multistate flow network composed of multistate components (edges and nodes). In particular, each component has both capacity and cost attributes. Both types of commodity, which are transmitted through the same network simultaneously, consume the capacities of edges and nodes differently. That is, the capacity weight varies with types of commodity, edges and nodes. We first define the system capacity as a 2-tuple vector and then propose a performance index, the probability that the upper bound of the system capacity is a given pattern subject to the budget constraint. Such a performance index can be easily computed in terms of upper boundary vectors. An efficient algorithm based on minimal cuts is thus presented to generate all upper boundary vectors. The manager can apply this performance index to measure the quality level of supply-demand systems such as computer, logistics, power transmission, telecommunication and urban traffic systems.     

Transmission reliability of k minimal paths within time threshold

The quickest path problem involving two attributes, the capacity and the lead time, is to find a single path with minimum transmission time. The capacity of each arc is assumed to be deterministic in this problem. However, in many practical networks such as computer networks, telecommunication networks, and logistics networks, each arc is multistate due to failure, maintenance, etc. Such a network is named a multistate flow network. Hence, both the transmission time to deliver data through a minimal path and the minimum transmission time through a multistate flow network are not fixed. In order to reduce the transmission time, the data can be transmitted through k minimal paths simultaneously. The purpose of this paper is to evaluate the probability that d units of data can be transmitted through k minimal paths within time threshold T. Such a probability is called the transmission reliability. A simple algorithm is proposed to generate all lower boundary points for (d, T), the minimal system states satisfying the demand within time threshold. The transmission reliability can be subsequently computed in terms of such points. Another algorithm is further proposed to find the optimal combination of k minimal paths with highest transmission reliability.     

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.     

Two-commodity reliability evaluation of a stochastic-flow network with varying capacity weight in terms of minimal paths

A real-life manufacturing system can be modeled as a stochastic-flow network in which nodes stand for the machine stations, and arcs stand for the shipping media. In terms of minimal paths (MPs), this paper presents a stochastic-flow network model with four characteristics: (1) both nodes and arcs have multiple possible capacities, and may fail; (2) each component (arc/node) has both capacity and cost attributes; (3) two-commodity are proceeded; and (4) the capacity weight varies with arcs, nodes, and types of commodity. We study the possibility of two-commodity to be transmitted through this network simultaneously under the budget constraint. Such a possibility is named as the system reliability. The MPs play the role of media to describe the relationship among flow assignments and capacity vectors. Subsequently, a simple algorithm, in terms of MPs, is proposed to evaluate the system reliability. From the capacity management and decision making viewpoints, managers may adopt the system reliability as a performance index to measure the system capacity and finally to determine if it meets the customers’ orders or not.     

带长度约束的k端网络可靠性分析

在网络视频和实时通信应用中需要研究带长度约束的k端网络可靠性分析问题,即任意两端点之间在给定时间延迟D约束内的k端网络可靠性。对带长度约束的k端网络可靠性问题进行了研究,主要是在传统不带路径约束的双端和k端网络可靠性研究基础上,提出了基于截断的路径约束方法;并根据该方法构造二元决策图BDD模型进行带约束的k端网络可靠性分析。该算法针对k端点对点信息流在一定时间延迟下完成传输问题,具有较强的实际意义。实例分析结果验证了本方法的可行性和有效性。     

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.     

Online multiple objects tracking with detection reliability prior constraint

Multi-object tracking (MOT) is one popular topic in computer vision. It remains a challenging problem in complex scenes, especially of objects with similar appearance. In this case, many existing data association strategies, which link detections among consecutive frames according appearance and motion cues, may fail to track due to unreliable detections or confused appearance and motion. To solve this problem, this paper proposed a novel online multi-object tracking method with detection reliability prior constraint. Our method integrates the trajectory estimation and detection-prediction association into a unified framework. The detection reliability prior constraint is built with the Hankel matrix from object motion model. When we build the Hankel matrix, we adaptively select a set of previous frames to predict object states and calculate the associated weights between detections and candidate objects. Data association in MOT then is estimated by maximum a posteriori (MAP) in a Bayesian framework, accompanied with both previous trajectory and the current detection reliability. Experimental results using synthetic dataset and four public challenging datasets demonstrate that, the proposed method has a good tracking performance compared with the state-of-the-art multi-object trackers.     

考虑容量和时延约束的网络端端可靠性研究

早期对网络可靠性的研究主要是以连通性为网络功能来研究的,并没有考虑网络完成用户需求的能力。综合考虑网络容量以及时延约束,在网络部件（节点或边）的容量约束下改变网络的拓扑结构,通过改进的节点遍历法,将满足用户时延约束的有效最小路集输出,通过BDD算法对有效路集进行不交化,得出网络端端可靠度的精确值。算法采用Matlab程序实现,为评估加权网络可靠性提供了一种新方法。     

Reliability evaluation of a multistate flexible flow shop with stochastic capacity for multiple types of jobs

A flexible flow shop (FFS) is a general manufacturing system that has been studied by numerous researchers. Owing to maintenance, partial failure, the possibility of failure, unexpected situations, etc., the number of functioning machines in a stage should be represented by multiple levels. It is appropriate to regard the capacity in each stage (i.e., the number of machines in a stage) as stochastic. Unlike the previous research, which dealt with the FFS problems under the assumption of the fixed capacity, this paper extends the deterministic capacity to the stochastic case in every stage. The FFS with stochastic capacity is modeled as a multistate flexible flow shop network (MFFSN), where each edge denotes a stage with stochastic capacity and each node denotes a buffer. The addressed problem is to evaluate network reliability, the probability that the MFFSN can complete a customer's order composed of multiple types of jobs within a time threshold. An efficient algorithm integrating a systematic branch-and-bound approach is proposed to obtain the lower boundary vectors, in terms of a pair of capacity vectors generated from two estimated demand vectors. Two practical cases, a tile production system and an apparel manufacturing system, are presented to demonstrate the proposed algorithm and to discuss the changes in network reliability within different time thresholds, respectively.     

遗传算法在可靠性约束的光网络带宽分配中的应用

光网络中广泛使用OSPF作为路由协议,这使得路由选择智能化.然而,如何根据既定的网络拓扑和业务量规划各链路带宽及其可靠性成为一个难题,在综合考虑网络成本和可靠性的基础上,给出了两种链路带宽算法,即迭代法和遗传算法.在设计带宽遗传算法时,提出将带宽分解为两个指标(相对尺度和绝对尺度),从而解决了编码经各种遗传运算仍为可行解的问题.从实验结果看出,带宽遗传算法能很好地逼近最优解,结果令人满意.     

基于DHT发现端到端多条覆盖网路径的方法

为进一步提高端到端数据传输的吞吐率,提出基于DHT发现多条覆盖网路径的方法.一条覆盖网路径由若干跳构成,而数据吞吐率依赖各跳传输性能的瓶颈.为消除瓶颈,根据数据到达结点的吞吐率选择往返延迟时间较小的若干下一跳结点,使得数据不会在该结点拥塞.结点DHT维护着到各下一跳结点的往返延迟时间,基于DHT可发现端-端多条覆盖路径,从而实现并行数据传输.实验结果表明,该方法可找到适合的多条端到端路径,并行传输可取得比单路径传榆更大的吞吐率.     

Topological optimization models for communication network with multiple reliability goals

Network reliability models for determining optimal network topology have been presented and solved by many researchers. This paper presents some new types of topological optimization model for communication network with multiple reliability goals. A stochastic simulation-based genetic algorithm is also designed for solving the proposed models. Some numerical examples are finally presented to illustrate the effectiveness of the algorithm.     

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.     

A method to evaluate the routing policy with two minimal paths within time threshold

Two attributes, the capacity and the lead time, are involved in the quickest path problem which finds a path with the minimum transmission time. The capacity of each edge is assumed to be deterministic in this problem. However, in many real-life networks such as computer, telecommunication, logistics networks, etc., each edge should be multistate due to failure, maintenance, etc. Such a network is named a multistate network. Hence, the minimum transmission time through a multistate network is not fixed. We evaluate the system reliability that a specified amount of data can be sent through a pair of minimal paths simultaneously within the time threshold. A solution procedure is first proposed to calculate it. In order to boost the system reliability, the network administrator decides the routing policy in advance to indicate the first and the second priority pairs of minimal paths. The second one will be responsible for the transmission duty if the first one fails. According to the routing policy, the system reliability can be subsequently computed. The case to transmit data through more than two minimal paths can be extended easily.     

Distributed workflow mapping algorithm for maximized reliability under end-to-end delay constraint

A distributed scientific workflow mapping algorithm for maximized reliability under certain end-to-end delay (EED) bound is proposed. It is studied in a heterogeneous distributed computing environment, where computing node and communication link failures are inevitable. The mapping decision and the stored table information is distributed among various nodes in order to achieve scalability and robustness, which are especially important for large-scale distributed systems. This Distributed Reliability Maximization workflow mapping algorithm under End-to-end Delay constraint (dis-DRMED) considers both the maximum reliability and the minimum EED objectives in a two-step procedure. In the first step, a mapping algorithm combining iterative Critical Path search and Layer-based priority assigning techniques (CPL) is adopted to minimize the EED by focusing on the optimal allocation of tasks on the critical path. In the second step, tasks on noncritical paths are remapped to improve the overall execution reliability. Simulation results under various system setups demonstrated that dis-DRMED achieved considerably higher reliability values under the same EED constraint compared with some representative workflow mapping algorithms.