System Reliability of a Limited-Flow Network in Multicommodity Case

Network analysis is an important approach to model real-world systems. System reliability, and system unreliability are two related performance indices useful to measure the quality level of a supply-demand system. For a binary-state network without flow, the system unreliability is the probability that the system can not connect the source and the sink. Extending to a limited-flow network in the single-commodity case, the arc capacity is stochastic, and the system capacity (i.e. the maximum flow) is not a fixed number. The system unreliability for (d+1), the probability that the upper bound of the system capacity equals d, can be computed in terms of upper boundary points. An upper boundary point is the maximal system state such that the system fulfills the demand. This paper concentrates on a multicommodity limited-flow network (MLFN) in which multicommodity are transmitted through unreliable nodes and arcs. Nevertheless, the system capacity is not suitable to be treated as the maximal sum of the commodity because each commodity consumes the capacity differently. We define the system capacity as a demand vector if the system fulfills at most such a demand vector. The main problem of this paper is to measure the quality level of a MLFN. We propose a new performance index, the probability that the upper bound of the system capacity equals the demand vector subject to the budget constraint, to evaluate the quality level of a MLFN. A branch-and-bound algorithm based on minimal cuts is presented to generate all upper boundary points in order to compute the performance index. The computational complexity of the proposed algorithm is analyzed     

An algorithm for lower reliability bounds of multistate two-terminal networks

Network reliability is extensively used to measure the degree of stability of the quality of infrastructure services. The performance of an infrastructure network and its components degrades over time in real situations. Multi-state reliability modeling that allows a finite number of different states for the performance of the network and its components is more appropriate for the reliability assessment, and provides a more realistic view of the network performance than the traditional binary reliability modeling. Due to the computational complexity of the enumerative methods in evaluating the multi-state reliability, the problem can be reduced to searching lower boundary points, and using them to evaluate reliability. Lower boundary points can be used to compute the exact reliability value and reliability bounds. We present an algorithm to search for lower boundary points. The proposed algorithm has considerable improvement in terms of computational efficiency by significantly reducing the number of iterations to obtain lower reliability bounds.     

基于神经网络和点的重要性度量的边缘提取方法

本文从边缘点所在尺度和其邻域的灰度分布状况入手,提出了一个由四个分量组成的、对应于点的、用于衡量该点重要性的边缘重要性度量向量,为了考虑应用背景,用人工分类好的样本对一BP神经网络进行训练,用训练好的网络对图像的边缘点依重要性进行分类,从而获得图像的重要边缘。另外由于本文的方法无须对图像进行卷积,所以不会产生边缘偏移。经实验验证此方法取得了良好的效果。     

Reliability of a Flow Network Subject to Budget Constraints

The system capacity of a deterministic flow network is the maximum flow from the source to the destination. In a single-commodity stochastic-flow network (branches all have several possible capacities, and may fail), the system reliability, the probability that the maximum flow is larger than or equal to a given demand, is an important performance index to measure the quality level of a network. In a two-commodity stochastic-flow network, different types of commodities are transmitted through the same network simultaneously, and compete for the capacities. We concentrate on the reliability problem for such a network subject to the budget constraint. This paper defines firstly the system capacity as a pattern. We propose a performance index, the probability that the system capacity is less than or equal to a given pattern subject to the budget constraint, to evaluate the system performance. A simple algorithm based on minimal cuts is proposed to generate all maximal vectors meeting the demand and budget constraints. The performance index can then be computed in terms of all such maximal vectors     

Reliability of a stochastic-flow network with unreliable branches & nodes, under budget constraints

System reliability evaluation for flow networks is an important issue in quality management. This paper concentrates on a stochastic-flow network in which nodes as well as branches have several possible capacities, and can fail. The possibility is evaluated that a given amount of messages can be transmitted through the stochastic-flow network under the budget constraint. Such a possibility, system reliability, is a performance index for a stochastic-flow network. A minimal path, an order sequence of nodes & branches from the source to the sink without cycles, is used to assign the flow to each component (branch or node). A lower boundary point for (d, C) is a minimal capacity vector, which enables the system to transmit d messages under the budget C. Based on minimal paths, an efficient algorithm is proposed to generate all lower boundary points for (d, C). The system reliability can then be calculated in terms of all lower boundary points for (d, C) by applying the inclusion-exclusion rule. Simulation shows that the implicit enumeration (step 1) of the proposed algorithm can be executed efficiently.     

A petri net approach for the enumeration of all K-trees and K-cutsets and its application on K-terminal network reliability evaluation

This paper determines the overall reliability of computer networks in which m-level hierarchical routing strategies are used for the communication between their nodes. Also, the clusters have dynamic boundaries, i.e. when a cluster is decomposed the network reacts by reorganizing itself into a new set of clusters in order to continue to communicate, if possible, with the components of the decomposed subnetwork.The proposed method first enumerates all the minimal cutsets and then evaluates very efficiently the overall reliability. The presented technique is very useful when large computer networks or many interconnected networks are examined.     

Reliability evaluation for distributed computing networks withimperfect nodes

This paper examines two compensating methods that: (1) account for imperfect nodes, and (2) can be embedded in most symbolic network reliability algorithms that presume perfect nodes. The Aggarwal method can be exponential in time with the number of links, whereas the Torrieri method is always linear. However the Torrieri method can yield incorrect results for some undirected networks. This paper points out such incorrectness and then proposes an efficient reliability evaluation algorithm (ENR/KW) accounting for imperfect nodes in distributed computing networks. Based on the concept of network partition, ENR/KW exploits some simple efficient techniques to handle the unreliable nodes, for directly computing the network reliability expression considering imperfect nodes instead of using any compensating method. The basic idea of ENR/KW is to partition the network directly into a set of smaller disjoint subnetworks by only considering link elements as if all nodes are perfect. Each disjoint subnetwork is generated by maintaining a specific directed graph structure to consider the effect of imperfect nodes. Therefore, the reliability expression for imperfect nodes can be obtained directly from the disjoint subnetwork and the specific directed graph. ENR/KW can be generalized to evaluate various network reliability measures considering imperfect nodes such as terminal-pair reliability, K-terminal reliability, and distributed-program reliability. Many experiments for evaluating the terminal-pair reliability and distributed-program reliability were performed on a SUN workstation to show the efficiency of ENR/KW in terms of the number of generated subnetworks and overall computation time     

基于全卷积网络的红外图像非均匀性校正算法

针对红外成像系统在经过两点校正后,随时间漂移仍然会出现的非均匀性噪声,提出一种基于全卷积深度学习网络的红外图像非均匀性校正算法,使用子网络与主网络相结合的方式进行非均匀性校正.该算法设计了非均匀性等级估计子网络,将含有非均匀性噪声的红外图像输入子网络后,输出非均匀性等级估计图,并和待校正红外图像一并输入校正主网络.子网...     

一种计算随机流网络可靠性的新算法

提出了一种计算随机流网络可靠性的新方法。通过一定的规则生成网络的状态树，使得每一个分支都是全序集合。在生成状态树的同时搜索每一个分支，对状态采用基于割集的方法进行判断。每个分支上的最小的有效状态就是网络的d-下界点。求得所有的d-下界点，进而求出网络的可靠性。     

An Efficient Algorithm for Deducing the Minimal Cuts and Reliability Indices of a General Network Configuration

The paper describes an efficient algorithm for evaluating the minimal cut sets of any general network. The algorithm is based on Boolean algebra and set theory, and contains many important improvements. The four most important features are 1. only one set of topological input data is required to evaluate the minimal cuts and reliability indices of every output node; 2. a mix of undirectional, bidirectional and multi ended components can be included very simply; 3. any number of input nodes may be specified; 4. a new concept of overall system reliability permits different, large, and complex systems to be compared. The computational efficiency of the algorithm is clearly indicated by the fact that the time required to analyse Example 1 on a CDC7600 was 0.7 sec. The storage required with the appropriate arrays dimensioned for a system having 100 components and up to 125 minimal cut sets per output node is 15 k-words. These times and storage include the overall system reliability analysis.     

An efficient method for evaluating network-reliability withvariable link-capacities

An efficient method is proposed to evaluate the network reliability with variable link capacities when the simple paths of the network are known. Most of the evaluation techniques proposed in the literature so far are based on enumerating the k-composite paths, each of which is a union of k simple paths. Although some of those methods lead to correct results, the redundancy is still quite large and may occur repeatedly each time the higher order composite paths are generated. This paper proposes a new method based on the concepts of additivity and eligibility properties defined in the text. The authors identify a composite path as a subnetwork which in general contains more simple paths than those involved in composition, and add only a minimal set of links at each step which gives maximal increase on the maximum capacity flow of the subnetwork. Thereby, they reduce the possible occurrence of redundancy significantly. The number of composite paths considered for the capacity computation is also greatly reduced. Furthermore, it is not necessary to keep the information on how many and which simple paths have been used in each composite path. Some numerical examples illustrate the efficiency of the method     

基于点特征传递的电力设备部件激光点云补全网络

针对电力场景下因激光雷达扫描范围有限、电力设备部件相互遮挡等因素导致电力设备部件点云缺失的问题,提出了基于点特征传递的电力设备部件激光点云补全网络PPC Net(Power Point cloud Complete Net)。该网络使用多尺度特征融合编码器提取不同尺度输入残缺点云的全局和局部特征,以避免多维度映射特征导致的电力设备部件细节特征丢失问题,并引入EdgeConv加强对点云邻域信息提取;在精细完整点云生成阶段提出DT模块整合父级点到子级点的特征传递,以保留生成点云的局部特征;设计平滑优化模块,经三级平滑采样算法输出分布均匀、表面平滑的电力设备部件完整点云。在自建电力设备部件点云数据集ELE及公开数据集PCN上实验表明,PPC Net对残缺的电力设备部件点云有较好的补全效果,并在一般形状点云上有良好泛化性。     

Sequential capacity determination of subnetworks in network performance analysis

In the process of performance evaluation for a stochastic network whose links are subject to failure, subnetworks are repeatedly generated to reflect various states of the network, and the capacity of each subnetwork is to be determined upon generation. The capacity of a network is the maximum amount of flow which can be transmitted through the network. Although there are existing algorithms for network capacity computation, it would create a great number of repetitions to compute the capacity of each subnetwork anew upon generation in the process. This is true because subnetworks are generated by combining certain links to the current one, and hence each current subnetwork is embedded in those new subnetworks. Recently, a number of methods have been proposed in the context of searching a method which efficiently computes the capacity of subnetworks by utilizing the given information of minimal paths, and preferably without many repetitions in sequential computations. But, most of the methods still have drawbacks of either failing to give correct results in certain situations, or computing the capacity of each subnetwork anew whenever the subnetwork is generated. In this paper, we propose a method based on the concepts of signed minimal path, and unilateral link, as defined in the text. Our method not only computes the capacity of each subnetwork correctly, but also eliminates the repetitive steps in sequential computations, and thereby efficiently reduces the number of subnetworks to consider for capacity computation as well. Numerical examples are presented to illustrate the method. The drawbacks of other methods are also discussed with counter examples.     

开关电容网络故障的子网络级诊断

本文基于电荷守恒原理,给出了一种开关电容网络(SCN)的故障子网络诊断算法.它能识别出故障子网络或者确定出包含故障子网络的子网络集合,适用于大规模的多相SCN.     

一个计算无圈有向网络可靠度的新算法

本文对无圈有向网络的可靠度计算进行了研究。提出了加权有序根树的概念，给出了路径集合的一种特殊排序方法，导出一个计算无圈有向网络可靠度的拓扑公式。在该公式的基础上提出了一个新的计算无圈有向网络可靠度的不交积和算法，算法可以生成简洁的可靠度表达式，从而可以有效地计算无圈有向网络的可靠度。同时验证了算法的有效性。     

Reliability evaluation of a limited-flow network in terms ofminimal cutsets

Many systems can be regarded as flow networks whose arcs have discrete and multi-valued random capacities. The probability of the maximum flow at each various level and the reliability of such a flow network can be calculated in terms of K-lattices which are generated from each subset of the family of all MCs (minimal cutsets). However the size of such a family 2^m-1 (m=number of MCs) grows exponentially with m. Such a flow network can be considered as a multistate system with multistate components so that its reliability can be evaluated in terms of upper boundary points of each level d (named d-MCs here). This work presents an algorithm to generate all d-MCs from each MC for each system capacity level d. The new algorithm is analyzed and compared with the algorithm given by J. Xue (1985). Examples show how all d-MCs are generated; the reliability of one example is computed     

Siamese target estimation network with AIoU loss for real-time visual tracking

The fully convolutional siamese network based trackers achieve great progress recently. Most of these methods focus on improving the capability of siamese network to represent the target. In this paper, we propose our model which focuses on estimating the state of the target with our proposed novel IoU (intersection over union) loss function which is named AIoU. Our model consists of a siamese subnetwork for feature extraction and a target estimation subnetwork for state representation. The target estimation subnetwork contains a classification head for classifying background and foreground and a regression head for estimating target. In order to regress better bounding boxes, we further study the loss function utilized in the regression head and propose a powerful IoU loss function. Our tracker achieves competitive performance on OTB2015, VOT2018, and VOT2019 benchmarks with a speed of 180 FPS, which proves the effectiveness of our method.     

Reliability Analysis of a Communication Network with Multimode Components

This paper presents a model to calculate the reliability of communication networks with multimode components. Previous research on network reliability has focused on models in which each component may be in one of two modes, namely, operative or failed. In reality, a component may undergo degradations in performance before a complete outage, and will therefore operate in more than two modes. Traditional network reliability measures, such as the probability that a pair of nodes is connected, are not meaningful in a multimode model. Therefore, the mean message delay of the network is defined as the performance measure. An exact calculation of this reliability measure is not feasible due to the large number of network states, corresponding to network components being in different modes. We have developed an approximation method to calculate this reliability measure. This method requires us to work with the states of the network in order of decreasing probability. An algorithm ORDER-Mis developed to generate these states in the proper order.     

IP over WDM网络最小功耗模型和休眠机制研究

针对IP over WDM网络,建立了整数线性规划(ILP)最小功耗模型,计算了满足峰值业务需要开启的设备数目;对于低峰业务提出休眠机制,分别利用最小光路数算法与最小跳数算法,在保证连接无阻塞的情况下找出空闲设备,对比峰值业务得到不同算法下的设备使用率,确定IP over WDM网络的节能潜力。结果表明,ILP优化模型的网络功耗最小,最小光路数算法次之;低峰业务下利用休眠机制可以关闭设备的比例占40%～60%;采用最小光路数算法的休眠机制节能效果较优。     

Estimation of reliability for communication/computer networkssimulation/analytic approach

A general simulation/analytic approach for jointly assessing the reliability and performance of a communication/computer network is proposed. The advantages of this approach are the following: (a) it allows consideration of a variety of performance measures, (b) it allows consideration of a general structure of network components failure distribution, (c) it reduces complexity of the model and related calculations, (d) it is relatively simple to implement, and (e) it can derive sensitivity information about network performance with respect to various parameters-the first step for an effective network optimization algorithm. The method is illustrated in a number of examples using network connectivity and weighted network bandwidth as a measure of performance