Capacity Efficiency and Restorability of Path Protection and Rerouting in WDM Networks Subject to Dual Failures

Resilient optical networks are predominately designed to protect against single failures of fiber links. But in larger networks, operators also see dual failures. As the capacity was planned for single failures, disconnections can occur by dual failures even if enough topological connectivity is provided. In our approach the design of the network minimizes the average loss caused by dual failures, while single failures are still fully survived. High dual failure restorability is the primary aim, capacity is optimized in a second step. For WDM networks with full wavelength conversion, we formulate mixed integer linear programming models for dedicated path protection, shared (backup) path protection, and path rerouting with and without stub-release. For larger problem instances in path rerouting, we propose two heuristics. Computational results indicate that the connectivity is of much more importance for high restorability values than the overall protection capacity. Shared protection has similar restorability levels as dedicated protection while the capacity is comparable to rerouting. Rerouting surpasses the protection mechanisms in restorability and comes close to 100% dual failure survivability. Compared to single failure planning, both shared path protection and rerouting need significantly more capacity in dual failure planning.     

On Finding the Multicast Protection Tree Considering SRLG in WDM Optical Networks

In this letter, a new sharing mechanism, SRLG sharing, is proposed, which allows the links of the same shared risk link group (SRLG) in a primary light tree to share protections in WDM optical networks. In previous studies, how to share spare resources with SRLG constraints has not been studied in multicast optical networks. In this letter, considering SRLG sharing, we propose a novel algorithm –multicast with SRLG sharing (MSS)– to establish a protection light tree. Finally, the algorithm MSS and the algorithm multicast with no SRLG sharing (MNSS) are compared through a simulation to show that our new sharing scheme of SRLG sharing is more efficient than that of no SRLG sharing in terms of spare resource utilization and blocking probability.     

TCP Performance in Optical Packet-switched Networks

Optical packet assembly is a key function to support inter-working between TCP/IP networks and optical packet-switched networks. It is characterized by the assembly delay and by the segment aggregation needed to form an optical packet. These counter-balancing aspects depend on several environment variables, such as the TCP parameters, the access link speed, the optical packet size whose effects are studied in this paper. Performance evaluations are obtained by extensive simulations in terms of send rate of TCP flows, fairness, efficiency, and assembly delay. Some guidelines in the design of optical packets that take into account the results presented are given.     

Spin probe study of semi‐interpenetrating polymer networks based on polyurethane and polymethacrylate functional prepolymers

The motional transition and heterogeneity of semi‐interpenetrating networks (SIPNs) based on polyurethane (PU) with carboxylic groups and methacrylic copolymer (PM) with tertiary amine groups were studied by the electron spin resonance (ESR) spin probe method. The concentration of functional groups in both prepolymers varied from 0 to 0.45 mmol g^?1. Spin‐probed SIPNs show that the temperature‐dependent spectra are sensitive to polymer interactions imposed by functional groups. These interactions determine the free volume distribution in the matrix and temperature at which motional transition takes place. The fraction of free volume increases with functional group concentration and reaches its maximum at 0.25 mmol g^?1. Further increases in the functional group concentration reduce the free volume. The results of the networks with strong interactions are discussed in terms of the interference of the plasticizing effect of the PU component and the formation of possible cluster cross‐links, which restricts segmental motions. Copyright © 2003 Society of Chemical Industry     

多传感器目标的模糊识别

根据模糊理论，采用信息融合技术和模糊识别技术，讨论了在多类传感器网内进行多目标模糊识别的一般原理和方法。     

WDM网络光层保护新算法的探讨

首先介绍了几种按照不同标准划分的WDM网络光层保护方法,然后提出了三种实现光层保护的新算法,对它们的内容和性能做了详细描述。按照提出的算法所求得的解,可以为WDM网络提供新的光层保护方式。     

Process monitoring using auto-associative,feed-forward artificial neural networks

The potential of using artificially simulated neural networks as intelligent, adaptive process-monitoring devices is discussed. The investigation is considered as a method for automatic, intelligent exception reporting for quality control applications. The technique is also compared with the conventional statistical approaches of principal component analysis and Kohonen's feature map. The applications of the technique in aerospace and manufacturing environments are presented and a possible extension of the method to incorporate a diagnostic function is discussed.Seconded from Cheltenham and Gloucester College of Higher Education as a Royal Society/SERC Research Fellow at Smith's Industries Aerospace and Defence Systems, Bishop's Cleeve, Cheltenham, UK.     

停棒子系统与控制棒组操作范围监测试验

本文叙述了反应堆保护系统停棒与汽轮机降功率子系统的系统功能、保护参数和秦山核电站控制棒组插入监测器的设计与参数选择,确定了控制棒提升上极限值和在不同工况下棒插入低位、低-低位整定值,并在热态零功率条件下加以验证。试验证明参数选择是合理的,为功率运行阶段提供了数据。     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Artificial neural networks for coordination and control: The portability of experiential representations

It is time to locate connectionist representation theory in the new wave of robotics research. The utility of representations developed in artificial neural networks (ANNs) during learning has been demonstrated in cognitive science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a classifier net is trained with laser scan data to output transformationally invariant position classes; (ii) an arm net is trained for picking up objects; (iii) an inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalization of decentered viewpoints.