A Physarum-inspired approach to supply chain network design基于多头绒泡菌模型的供应链网络设计算法

A supply chain is a system which moves products from a supplier to customers, which plays a very important role in all economic activities. This paper proposes a novel algorithm for a supply chain network design inspired by biological principles of nutrients’ distribution in protoplasmic networks of slime mould Physarum polycephalum. The algorithm handles supply networks where capacity investments and product flows are decision variables, and the networks are required to satisfy product demands. Two features of the slime mould are adopted in our algorithm. The first is the continuity of flux during the iterative process, which is used in real-time updating of the costs associated with the supply links. The second feature is adaptivity. The supply chain can converge to an equilibrium state when costs are changed. Numerical examples are provided to illustrate the practicality and flexibility of the proposed method algorithm.     

Distributed fault tolerance in optimal interpolative nets

The recursive training algorithm for the optimal interpolative (OI) classification network is extended to include distributed fault tolerance. The conventional OI Net learning algorithm leads to network weights that are nonoptimally distributed (in the sense of fault tolerance). Fault tolerance is becoming an increasingly important factor in hardware implementations of neural networks. But fault tolerance is often taken for granted in neural networks rather than being explicitly accounted for in the architecture or learning algorithm. In addition, when fault tolerance is considered, it is often accounted for using an unrealistic fault model (e.g., neurons that are stuck on or off rather than small weight perturbations). Realistic fault tolerance can be achieved through a smooth distribution of weights, resulting in low weight salience and distributed computation. Results of trained OI Nets on the Iris classification problem show that fault tolerance can be increased with the algorithm presented in this paper.     

Regularizers for fault tolerant multilayer feedforward networks

Fault tolerance is an important issue for multilayer feedforward networks (MFNs). However, in the classical training approach for open node fault and open weight fault, we should consider many potential faulty networks. Clearly, if the number of faulty networks considered in the objective function is large, this training approach would be very time consuming. This paper derives two objective functions for attaining fault tolerant MFNs. One objective function is designed for handling open node fault while another one is designed for handling open weight fault. With the linearization technique, each of these two objective functions can be decomposed into two terms, the training error and a simple regularization term. In our approach, the objective functions are computationally simple. Hence the conventional backpropagation algorithm can be simply applied to handle these fault tolerant objective functions.     

Slime mould foraging behaviour as optically coupled logical operations

Physarum polycephalum is a macroscopic plasmodial slime mould whose apparently ‘intelligent’ behaviour patterns may be interpreted as computation. We employ plasmodial phototactic responses to construct laboratory prototypes of NOT and NAND logical gates with electrical inputs/outputs and optical coupling in which the slime mould plays dual roles of computing device and electrical conductor. Slime mould logical gates are fault tolerant and resettable. The results presented here demonstrate the malleability and resilience of biological systems and highlight how the innate behaviour patterns of living substrates may be used to implement useful computation.     

提高冗余服务性能的动态容错算法

针对分布式应用的性能要求,引入了负载平衡机制,以便对activere plication和primary backup容错算法进行权衡.提出一种基于冗余服务的动态容错算法RAWA(read-any-write-any),能根据系统负载状况动态改变请求的quorum,不但提高了请求的处理速度,而且以一种简单、有效的方式实现了负载平衡.结合所提出的一致性维护和互斥访问机制,该算法可以适用于嵌套访问和状态服务.另外,还分析了RAWA算法的性能,并通过在CORBA平台上与其他容错算法的对比测试,证明RAWA算法在     

分布、实时、容错一体化设计方法研究

针对分布式航天器系统的运行环境和特点，对嵌入式系统在空间环境、实时、容错、分布上的需求进行了分析，提出了分布、实时、容错一体化的嵌入式系统设计方法，从满足实时要求下的实时容错能力、免疫与自愈相结合的综合容错能力、单节点的容错与节点间容错相结合的分布容错能力和多种容错方法集成等4个方面，对设计方法进行了阐述。     

A regular scalable fault tolerant interconnection network for distributed processing

Bounded degree networks like deBruijn graphs or wrapped butterfly networks are very important from VLSI implementation point of view as well as for applications where the computing nodes in the interconnection networks can have only a fixed number of I/O ports. One basic drawback of these networks is that they cannot provide a desired level of fault tolerance because of the bounded degree of the nodes. On the other hand, networks like hypercube (where degree of a node grows with the size of a network) can provide the desired fault tolerance but the design of a node becomes problematic for large networks. In their attempt to combine the best of the both worlds, authors in [IEEE Transactions on Parallel and Distributed Systems 4(9) (1993) 962] proposed hyper-deBruijn (HD) networks that have many additional features of logarithmic diameter, partitionability, embedding, etc. But, HD networks are not regular, are not optimally fault tolerant and the optimal routing is relatively complex. Our purpose in the present paper is to extend the concepts used in the above-mentioned reference to propose a new family of scalable network graphs that retain all the good features of HD networks and at the same time are regular and maximally fault tolerant; the optimal point to point routing algorithm is significantly simpler than that of the HD networks. We have developed some new interesting results on wrapped butterfly networks in the process.     

一种具有容错能力的自适应神经网络分类器

在国内外容错型神经网络的基础上,提出了一种具有容错能力的自适应神经网络FTART4。该算法针对解决多点断路故障容错性的难点,提出了一种独特的增加网络冗余的方法,通过确定故障敏感点达到了冗余度与容错性的平衡。同时对FTART4神经网络解决多点断路故障问题进行了严谨的形式化分析,给出了FTART4算法的完整描述。采用通用的神经网络测试数据对算法进行了测试,实验结果表明该方法取得了较好的效果。     

具有间歇性观测的无线传感器网络分布式容错目标跟踪

针对具有随机间歇性观测的无线传感器网络, 基于多模型估计方法和一致性信息滤波器, 提出一种对观测节点故障容错的自适应分布式目标跟踪方法. 将传感器节点随机间歇性观测丢失和到达过程建模为马尔科夫切换系统, 在容积信息滤波器框架下, 估计传感器节点的观测丢失和到达的后验概率. 通过观测状态概率组合计算每个局部传感器节点的信息贡献, 基于自适应多模型估计方法, 实现对间歇性观测的容错性. 仿真结果表明了所提出算法的有效性和对间歇性观测的自适应容错性.

     

NFRL:一种分布系统的实时容错调度算法

在硬实时系统的应用中,如果硬实时任务不能在规定的时限完成,将会产生人员伤亡, 失等严重后果,为了保证在系统出错的情况下,硬实时任务仍然在能戴止时限之前完成,必须研究实时容错技术。本文从实时容错调度算法的角度出发,提出一种基于分布式系统的实时容错调度算法,并研究了该算法的时间复杂度,同时给出一个实例说明该容错调度算法的调度过程。这种容错调算法称为“无容错需求后调度算法（ＮＦＲＬ）,该实时容错调度算法     

Torus网络自适应容错路由算法

在应用于大规模并行计算机的互连网络的设计中,容错问题是其中的一个关键问题和难点问题。提出了一种基于Torus虫孔交换网络的容错路由算法,这一算法使用了矩形故障模型,无论故障区域大小多少和如何分布,算法始终是无死锁的,而且具有足够的自适应性,只要故障节点没有断开网络的连接,算法就能够通过选路使消息绕过故障区域,保持路由的连通性。同时,算法仅需要使用3个额外的虚拟通道。最后算法在不同故障率的Torus网络中进行了仿真实验,结果显示这一算法具有良好的平滑降级使用的特性。     

无人机系统自平衡容错控制与故障诊断

随着无人机的广泛普及和自主控制技术的深入研究,现代战争已经离不开无人机的身影。而无人机在其拥有特殊优势的同时也需要更多的维护来确保无人机执行任务过程中的安全。本文引入生物学思想中的自平衡理论,进行无人机容错控制与故障诊断系统设计,通过设计“平衡点”确定无人机的安全状态,并建立基于原始内驱力和次要内驱力的自平衡理论模型,将容错控制与故障诊断不仅应用于故障预测和健康管理,更创新提出将容错控制与故障诊断作为判断无人机是否可作为攻击时自杀武器的判据。仿真试验表明,无人机在穿越敌占区时,可根据自身的故障情况判断是否可以返航或作为自杀式武器,证明了算法的有效性。     

Automating the addition of fault tolerance with discrete controller synthesis

Discrete controller synthesis (DCS) is a formal approach, based on the same state-space exploration algorithms as model-checking. Its interest lies in the ability to obtain automatically systems satisfying by construction formal properties specified a priori. In this paper, our aim is to demonstrate the feasibility of this approach for fault tolerance. We start with a fault intolerant program, modeled as the synchronous parallel composition of finite labeled transition systems; we specify formally a fault hypothesis; we state some fault tolerance requirements; and we use DCS to obtain automatically a program, having the same behavior as the initial fault intolerant one in the absence of faults, and satisfying the fault tolerance requirements under the fault hypothesis. Our original contribution resides in the demonstration that DCS can be elegantly used to design fault tolerant systems, with guarantees on key properties of the obtained system, such as the fault tolerance level, the satisfaction of quantitative constraints, and so on. We show with numerous examples taken from case studies that our method can address different kinds of failures (crash, value, or Byzantine) affecting different kinds of hardware components (processors, communication links, actuators, or sensors). Besides, we show that our method also offers an optimality criterion very useful to synthesize fault tolerant systems compliant to the constraints of embedded systems, like power consumption.     

Physarum computing and topology optimisation

The plasmodium stage of the giant single-celled amoeboid organism Physarum polycephalum, or true slime mould, dynamically adapts its body plan in response to environmental stimuli, including nutrient location, temperature gradients, light exposure, and predatory threats. The construction and adaptation of the plasmodial transport network has been shown to be an efficient trade-off between minimising network distance and maximising connectivity. Optimisation of topology is also a desired trait in manufacturing and engineering, whereby the topology of an initially simple component is modified to minimise one or more properties (for example minimising the amount of substrate reduces the weight and material cost of the component) whilst maintaining other desired material properties within the component (for example strength under specific load points and conditions). Biologically inspired approaches to certain specific engineering challenges are well documented and successful. In this paper we explore at a more general level whether a cross-pollination can occur between Physarum computing and Topology Optimisation. Using an interdisciplinary modelling approach we explore whether the evolution of transport networks in a multi-agent model of Physarum has any similarities to networks formed by Topology Optimisation. We find that the Topology Optimisation method generates networks which are similar to the model slime mould networks. The Topology Optimisation networks correspond to higher regions of the Toussaint hierarchy of proximity graphs (i.e. more edges) whereas the model slime mould networks exhibit greater minimisation of network length. Since it is possible to adjust network connectivity in the multi-agent model via nutrient concentration we speculate that similar parametric adjustment may be possible to alter the connectivity of Topology Optimisation networks.     

两种典型神经网络容错方法的比较

Behnam提出的SC算法和文中提出的rehidden算法是两种典型的前向神经网络容错 算法,前者改进BP算法进行学习,后者对已学习的网络进行隐层节点冗余.这两种算法各有优 缺点.文中对这两种算法进行了仿真实验分析,最终得到了每种算法适用的网络规模和硬件条 件,在不同环境下应采用不同的方法才能得到可行的容错网络.最后还对SC算法的一些改进进 行了讨论.     

Fault tolerant aggregation in heterogeneous sensor networks

Fault tolerance and scalability are important considerations in the design of sensor network applications. Data aggregation is an essential operation in sensor networks. Multiple techniques have been proposed recently to tackle the issues of scalability and fault tolerance of aggregation in sensor networks. In this article, we analyze the impact of using a few of the more reliable, though expensive, nodes–such as the Intel XScale–called microservers, in addition to the standard motes, on the fault tolerance and scalability of the aggregation algorithms in sensor networks. In particular, we propose a simple model that captures the essence of tree aggregation in such heterogeneous sensor networks. We validate this theoretical model with simulation results. We also study the effective impact on the sustainable probability of failure, and perform cost-benefit analysis. We also show how hybrid aggregation can be utilized instead of tree, to improve the performance of aggregation in heterogeneous sensor networks. We show that our work can be applied for effectively optimizing the use of expensive hardware while designing fault-tolerant, distributed sensor networks.     

Fault-tolerant wormhole routing for hypercube networks

We present an adaptive fault-tolerant wormhole routing algorithm for hypercubes by using 3 virtual networks. The routing algorithm can tolerate at least n−1 faulty nodes and can route a message via a path of length no more than the shortest path plus four. Previous algorithms which achieve the same fault tolerant ability need 5 virtual networks. Simulation results are also given in this paper.     

A coordination architecture for UUV fleets

This paper presents a modular and expandable architecture, which includes diversified functions and can be applied to heterogeneous fleets of unmanned underwater vehicles (UUVs), to solve the problem of decentralized formation coordination. The architecture is modular and each module is built such that it can solve a precise task using one or more functions. Three functions among them play a key role for the whole architecture: localization, faultless formation control and fault tolerance. The localization function is performed by the use of an adaptive extended Kalman filter (A-EKF) algorithm; the fault-free formation control function is based on a nonlinear decentralized model predictive control (ND-MPC) algorithm; the fault tolerance function is based on a hierarchy graph theory. The novelty of the paper lies in the use of the above mentioned functions as the core of an architecture which is expandable, decentralized and can be applied to a wide range of vehicles.     

可重构机械臂反演时延分散容错控制

针对存在模型参数不确定性的可重构机械臂系统执行器故障,提出一种基于反演设计与时延技术相结合的容错控制方法.该方法利用反演设计的基本思想,通过神经网络补偿子系统动力学模型中的参数不确定项和关联项.利用时延控制的逼近能力来补偿执行器的故障,使得故障发生时能及时实现容错控制.该方法具有不需要在线进行故障诊断的特点,仿真结果表明了所提出控制方法的有效性.     

Reliable multistage interconnection network design

High-performance supercomputers generally comprise millions of CPUs in which interconnection networks play an important role to achieve high performance. New design paradigms of dynamic on-chip interconnection network involve a) topology b) synthesis, modeling and evaluation c) quality of service, fault tolerance and reliability d) routing procedures. To construct a dynamic highly fault tolerant interconnection networks requires more disjoint paths from each source-destination node pair at each stage and dynamic rerouting capability to use the various available paths effectively. Fast routing and rerouting strategy is needed to provide reliable performance on switch/link failures. This paper proposes two new architecture designs of fault tolerant interconnection networks named as reliable interconnection networks (RIN-1 and RIN-2). The proposed layouts are multipath multi-stage interconnection networks providing four disjoint paths for all the source-destination node pairs with dynamic rerouting capability. The designs can withstand switch failures in all the stages (including input and output stages) and provide more reliability. Reliability analysis of various MIN architectures is evaluated. On comparing the results with some existing MINs it is evident that the proposed designs provides higher reliability values and fault tolerance.