Design of 4-disjoint gamma interconnection network layouts and reliability analysis of gamma interconnection Networks

Multistage interconnection networks (MINs) are widely used for reliable data communication in a tightly coupled large-scale multiprocessor system. High reliability of MINs can be achieved using fault tolerance techniques. The fault tolerance is generally achieved by disjoint paths available through multiple connectivity options. The gamma interconnection network (GIN) is a class of fault tolerant MINs providing alternate paths for source–destination node pairs. Various 2-disjoint and 3-disjoint GIN architectures have been presented in the literature. In this paper, two new designs of 4-disjoint paths multistage interconnection networks, called 4-disjoint gamma interconnection networks (4DGIN-1 and 4DGIN-2) are proposed. The proposed 4DGINs provide four disjoint paths for each source–destination pair and can tolerate three switches/link failures in intermediate interconnection layers. Proposed designs are highly reliable GIN with higher fault-tolerant capability than other gamma networks at low cost. Terminal pair reliabilities of proposed designs and various other 2-disjoint and 3-disjoint GINs are evaluated, analyzed and compared. Reliability values of proposed designs are found higher.     

Multicriterion network optimization problem

In this paper a multicriterion network optimization problem is discussed. The problem formulation is given and next the min-max principle of optimality is used in order to define the optimal path in the network. Then a method for seeking the optimal path in the network is described.     

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.     

Design and reliability analysis of fault-tolerant shuffle exchange gamma logical neighborhood interconnection network

The Journal of Supercomputing - Multistage interconnection networks are used as a medium for interconnecting processors and memories in multiprocessor systems. Multistage interconnection networks...     

Topology optimization of interconnection networks

This paper describes an automatic optimization tool that searches a family of network topologies to select the topology that best achieves a specified set of design goals while satisfying specified packaging constraints. Our tool uses a model of signaling technology that relates bandwidth, cost and distance of links. This model captures the distance-dependent bandwidth of modern high-speed electrical links and the cost differential between electrical and optical links. Using our optimization tool, we explore the design space of hybrid Clos-torus (C-T) networks. For a representative set of packaging constraints we determine the optimal hybrid C-T topology to minimize cost and the optimal C-T topology to minimize latency for various packet lengths. We then use the tool to measure the sensitivity of the optimal topology to several important packaging constraints such as pin count and critical distance.     

Uniform load sharing on a hierarchical content delivery network interconnection model

Content management system (CMS) is an infrastructure for efficient distribution, organization, and delivery of digital content. It is desirable that the content must be successfully delivered regardless of the end users location or attachment network. For the end to end delivery of content, a virtual open content delivery infrastructure is formed by interconnecting several CDNs. In this paper, we focus on content delivery network interconnection. An efficient and suitable to implement hierarchical CDNI architecture, named as HCDNI, is proposed to reduce the limitations of CDNIs. Next, a content distribution and redistribution scheme is proposed so that the searching time and the round trip time for the content delivery can be minimized. Next, we find a reliable and fault tolerant scheme for web server replica placement and content caching. Finally, analysis and simulation studies show that proposed algorithm results in a significant improvement in terms of data routing, path selection, content distribution and redistribution, load balancing and network scalability.     

Analytical model based on green criteria for optical backbone network interconnection

Key terms such as Global warming, Green House Gas emissions, or Energy efficiency are currently on the scope of scientific research. Regarding telecommunications networks, wireless applications, routing protocols, etc. are being designed following this new “Green” trend. This work contributes to the evaluation of the environmental impact of networks from physical interconnection point of view. Networks deployment, usage, and disposal are analyzed as contributing elements to ICT's (Information and Communications Technology) CO₂ emissions. This paper presents an analytical model for evaluating and quantifying the CO₂ emissions of optical backbone networks during their lifetime. The main goal of this work is to present the model and illustrate how to evaluate the physical interconnection of backbones from an environmental perspective. This model can be applied as a new type of decision support criteria for backbone's interconnection, since minimization of CO₂ emissions is becoming an important factor. In addition, two case studies are presented to illustrate the use and application of this model, and the need for de facto and international standards to reduce CO₂ emissions through good network planning.     

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.     

基于神经网络的级联软件可靠性模型

针对一般经典软件可靠性模型适用范围的局限性问题和预测精度问题,提出了一种新的级联模型.将4个经典软件可靠性模型的输出作为误差背向传播(error back propagation,BP)神经网络的输入,级联组合成一个软件可靠性模型,称之为级联软件可靠性模型.通过对一组经典的实际软件故障数据SYS1进行实验,将级联软件可靠性模型与4个经典软件可靠性模型预测的结果进行对比,结果表明级联软件可靠性模型的预测精度要远远高于4个经典软件可靠性模型,而且具有更好的通用性.     

一种混合粒子群算法的贝叶斯网络优化模型

传统的粒子群优化算法通过群体中粒子间的合作和竞争进行群体智能指导优化搜索,算法收敛速度快,但较易陷入局部较优值,进入早熟状态。为了解决这个问题,提出了一种混合粒子群算法的贝叶斯网络优化模型,它可以通过当前所选择的较优解群构造一个贝叶斯网络和联合概率分布模型,利用这个模型进行采样得到更优解,用其可随机替换掉PSO中的一些粒子或个体最优解;同时利用粒子群算法对当前选择出的较优解群进行深度搜索,并将得到的最优解融入到较优解群中。分析可知,该方法可以提高算法有效性和可靠性。     

Software reliability model with optimal selection of failure data

The possibility of obtaining more accurate predictions of future failures by excluding or giving lower weight to the earlier failure counts is suggested. Although data aging techniques such as moving average and exponential smoothing are frequently used in other fields, such as inventory control, the author did not find use of data aging in the various models surveyed. A model that includes the concept of selecting a subset of the failure data is the Schneidewind nonhomogeneous Poisson process (NHPP) software reliability model. In order to use the concept of data aging, there must be a criterion for determining the optimal value of the starting failure count interval. Four criteria for identifying the optimal starting interval for estimating model parameters are evaluated The first two criteria treat the failure count interval index as a parameter by substituting model functions for data vectors and optimizing on functions obtained from maximum likelihood estimation techniques. The third uses weighted least squares to maintain constant variance in the presence of the decreasing failure rate assumed by the model. The fourth criterion is the familiar mean square error. It is shown that significantly improved reliability predictions can be obtained by using a subset of the failure data. The US Space Shuttle on-board software is used as an example     

An optimization model for reverse logistics network under stochastic environment by using genetic algorithm

Recovery of used products has become increasingly important recently due to economic reasons and growing environmental or legislative concern. Product recovery, which comprises reuse, remanufacturing and materials recycling, requires an efficient reverse logistic network. One of the main characteristics of reverse logistics network problem is uncertainty that further amplifies the complexity of the problem. The degree of uncertainty in terms of the capacities, demands and quantity of products exists in reverse logistics parameters. With consideration of the factors noted above, this paper proposes a probabilistic mixed integer linear programming model for the design of a reverse logistics network. This probabilistic model is first converted into an equivalent deterministic model. In this paper we proposed multi-product, multi-stage reverse logistics network problem for the return products to determine not only the subsets of disassembly centers and processing centers to be opened, but also the transportation strategy that will satisfy demand imposed by manufacturing centers and recycling centers with minimum fixed opening cost and total shipping cost. Then, we propose priority based genetic algorithm to find reverse logistics network to satisfy the demand imposed by manufacturing centers and recycling centers with minimum total cost under uncertainty condition. Finally, we apply the proposed model to a numerical example.     

A unified approach to reliability and edge fault tolerance of cube-based interconnection networks under three hypotheses

The Journal of Supercomputing - The topological structures of the interconnection networks of some parallel and distributed systems are designed as n-dimensional hypercube $$Q_n$$ or n-dimensional...     

Multi-objective optimization problem under fuzzy rule constraints using particle swarm optimization

In this paper, a fuzzy multi-objective programming problem is considered where functional relationships between decision variables and objective functions are not completely known to us. Due to uncertainty in real decision situations sometimes it is difficult to find the exact functional relationship between objectives and decision variables. It is assumed that information source from where some knowledge may be obtained about the objective functions consists of a block of fuzzy if-then rules. In such situations, the decision making is difficult and the presence of multiple objectives gives rise to multi-objective optimization problem under fuzzy rule constraints. In order to tackle the problem, appropriate fuzzy reasoning schemes are used to determine crisp functional relationship between the objective functions and the decision variables. Thus a multi-objective optimization problem is formulated from the original fuzzy rule-based multi-objective optimization model. In order to solve the resultant problem, a deterministic single-objective non-linear optimization problem is reformulated with the help of fuzzy optimization technique. Finally, PSO (Particle Swarm Optimization) algorithm is employed to solve the resultant single-objective non-linear optimization model and the computation procedure is illustrated by means of numerical examples.     

随机网络的连通率研究

随机图是一种简单并且可用于抽象现实社会多种实际系统的网络。与其他网络模型不同,随机图的构造方式决定其节点具有对等性,且网络中可能存在孤立节点和子图。对随机图尤其是其连通性的研究有助于更深入地了解具有随机连接特性及节点对等特性的真实网络。文章采用理论与仿真相结合的方法,重点研究随机图的连通性和随机图连通率的计算方法,揭示了随机图在演化过程中的形态变化,表明随机图中树结构的广泛存在。研究还发现,在巨大连通子图形成前,随机图的子图大小呈幂律分布。本研究结果为复杂网络相关的实证研究和性质复杂的网络相变态研究提供了理论依据。     

独立故障串并联控制系统可靠性的最优化研究

研究了独立故障的串并联复式控制系统在单个或多个约束条件下的可靠性最优化问题。从系统的物理概念出发,提出了一种混合方法。按照连续变量平衡提高各级串联环节的可靠性,分析得出了在约束条件下各个环节的并联个数的计算公式和简化计算思路。     

Maintenance reliability estimation for a cloud computing network with nodes failure

The cloud computing network (CCN) has become a new paradigm for the business and clients as the development of information technology. To guarantee the CCN keep a good quality of service (QoS), the maintenance action is necessary when the CCN falls to a specific state such that it cannot afford enough capacity to meet demand d. In the CCN, edges and nodes have various capacities due to failure, partial failure, or maintenance; thus, the CCN has several possible states. This paper proposes an algorithm to estimate the performance of a CCN under maintenance budget with nodes failure. Hence, the maintenance reliability is developed to measure the capability that the CCN can send d units of data from the cloud to the client through multiple paths under the maintenance budget and time constraints. Furthermore, the system supervisor can conduct the sensitive analysis to improve/investigate the most important part in a large CCN afterwards.     

Robustness of star graph network under link failure

The star graph is an attractive underlying topology for distributed systems. Robustness of the star graph under link failure model is addressed. Specifically, the minimum number of faulty links, f(n, k), that make every (n − k)-dimensional substar S_n−k faulty in an n-dimensional star network S_n, is studied. It is shown that f(n,1)=n+2. Furthermore, an upper bound is given for f(n, 2) with complexity of O(n³) which is an improvement over the straightforward upper bound of O(n⁴) derived in this paper.     

基于BP神经网络的软件可靠性模型选择

软件可靠性模型是软件可靠性工程研究的一个重要方面.如何在缺乏可靠性数据的情况下,选择合适的软件可靠性模型是对软件可靠性进行量化分析的关键.参照软件可靠性模型评价准则,根据聚类思想,对失效数据编码,采用反向传播神经网络进行聚类计算,从而实现了软件可靠性模型的选择.最后通过仿真实验证明了该方法的正确性和有效性.