Optimal hypercube simulation on the partitioned optical passive stars network

Partitioned Optimal Passive Stars network, POPS(d,g), is an optical interconnection network of N processors (N=dg) with g ² optical passive star couplers. In this network, there are g groups of d processors each and the g ² couplers are used for connecting each group with each of the groups, including itself. In this paper, we present a technique for optimally simulating a frequently arising hypercube communication pattern on this network for all combinations of values of d and g. Specifically, we show that one-hop movements on the hypercube along the same dimension can be simulated on the POPS(d,g) network in slots for d≠g and in 2 slots for d=g.     

The partitioned optical passive stars network: simulations andfundamental operations

We show how a multiprocessor computer interconnected by a partitioned optical passive stars network (POPS) can simulate hypercube and mesh-connected computers. POPS algorithms for data sum, prefix sum, rank, adjacent sum, consecutive sum, concentrate, distribute, and generalize are also developed. These fundamental operations form the building blocks of parallel algorithms for many applications     

Hypercube computations on partitioned optical passive stars networks

This paper shows that an n=2/sup k/ processor partitioned optical passive stars (POPS) network with g groups and d processors per group can simulate every bidirectional move of an n processor hypercube using one slot when dg. Moreover, the same POPS network can simulate every monodirectional move of a processor hypercube using one slot when d=g. All these results are shown to be optimal. Our simulations improve on the literature whenever d/spl ne/g and directly yield several important consequences. For example, as a direct consequence of our simulations, a POPS network, n=dg and d相似文献   

Matrix multiplication of data routing using a partitioned opticalpassive stars network

We develop optimal or near optimal algorithms to multiply matrices and perform commonly occurring data permutations and BPC permutations on multiprocessor computers interconnected by a partitioned optical passive stars network     

光网络环境中最先开始路径优先的自适应路由算法

为了优化光网络环境下分布式计算系统的资源调度性能,提出了一种最先开始路径优先的自适应路由算法。该算法基于Dijkstra最短路径优先算法,通过引入一个时间标记变量来估计从源节点到当前目标节点的最先可用时间,绕过调度过程中产生拥堵的链路,选择能够最先开始通信的路由,从而减小通信竞争冲突,缩短了调度长度。仿真结果表明,该算法能够使用较少的网络链路资源来获得最短的调度长度。     

基于以太网无源光网络的1553B设备互联方法

分析了航空电子系统1553B总线的工作原理,提出一种新的基于以太网无源光网络(EPON)的1553B设备互联方案并且设计了相应的1553B网关。设计了基于BU-61580和MPC860的1553B网关,1553B网关用于实现1553B协议与EPON协议之间的数据转换,讨论了这种1553B设备互连方案中发现时隙分配和分组传输时延特性。     

Analysis on a mobile agent-based algorithm for network routing and management

Ant routing is a method for network routing in agent technology. Although its effectiveness and efficiency have been demonstrated and reported in the literature, its properties have not yet been well studied. This paper presents some preliminary analysis on an ant algorithm in regard to its population growing property and jumping behavior. Results conclude that as long as the value max, {i/spl Omega//sub j/|} is known, the practitioner is able to design the algorithm parameters, such as the number of agents being created for each request, k, and the maximum allowable number of jumps of an agent, in order to meet the network constraint.     

Managing manipulative and non-cooperative behaviors in large scale group decision making based on a WeChat-like interaction network

The main challenges in large scale group decision making (LSGDM) problem are how to tackle with the great number of participants and how to achieve a common solution accepted by most of group members. In LSGDM problems, some decision makers (DMs) will exhibit manipulative and non-cooperative behaviors owing to the different interests they might present. Dealing with such large group implies a need for mechanisms to detect DMs’ manipulative and non-cooperative behaviors, which might affect the overall efficiency of the consensus reaching process. This paper introduces a novel framework based on WeChat-like interaction network to analyze manipulative and non-cooperative behaviors in the LSGDM problems. In the developed framework, we first detect and manage the manipulative behaviors based on the interaction network. Afterwards, for the consensus model based on opinion evolution, we develop an approach to identify and manage non-cooperative behaviors under the WeChat-like interaction network context. As a result, both the DMs’ weights and trust network derived from it are dynamically updated in parallel. Detailed simulation experiments and comparison analysis under different input parameters are presented to demonstrate the efficiency of this novel approach for coping with manipulative and non-cooperative behaviors.     

考虑装卸频率的大规模车辆路径问题研究

通过分析大规模车辆路径问题的特点和求解难点,从我国的配送实践出发,引入装卸频率的概念,从新的视角认识大规模车辆路径问题,建立了考虑装卸频率的车辆路径优化多目标规划模型,并设计了改进的混合遗传算法进行求解。实验结果表明,该算法能够大幅降低企业配送成本和配送的装卸频率,具有实际参考价值和应用前景。     

Tabu search algorithm for routing,modulation and spectrum allocation in elastic optical network with anycast and unicast traffic

The paper presents a novel method based on the standard tabu search (TS) approach, dedicated to solve the routing, modulation and spectrum allocation (RMSA) problem in elastic optical networks (EONs). The considered formulation of the RMSA problem covers simultaneously unicast (one-to-one) and anycast (one-to-one-of-many) traffic demands. This is a very important issue taking into account the fact that anycasting gains more and more importance in contemporary Internet due the growing popularity of services like cloud computing, content delivery networks, and video streaming. In this paper, we formulate RMSA as an integer linear programming (ILP) problem and we study four different objective functions, which are related to, respectively, cost, power consumption, maximum and average spectrum usage. We evaluate the performance of our TS method based on the comparison with both optimal results yielded by the CPLEX solver and the results obtained by reference heuristic algorithms proposed in the literature. Moreover, we evaluate benefits of the use of anycasting in EONs. The performed simulation experiments demonstrate that the proposed algorithm outperforms other reference methods. What is more, we show that the anycast transmission can provide significant savings compared to the typical unicast transmission.     

低开销混合式保护的高可靠的波分/时分混合无源光网络

针对光纤故障参与保护倒换元器件多、保护资源开销大的问题,提出一种低开销混合式保护的高可靠波分/时分混合无源光网络(WDM/TDM-PON)结构。所提结构在光线路终端(OLT)中新设计了逻辑判定、备份收发以及保护路控制单元,使波分复用(WDM)部分只对故障部分器件执行倒换操作,实现了低开销的集中式保护;在时分复用(TDM)部分采用交叉总线形结构,实现了快速的分布式保护倒换。经分析证明,所提混合式保护结构有效地减少了保护资源开销,对馈入光纤(FF)、配线光纤(DF)和最后一个公里光纤(LMF)故障提供了1.5~2.4 ms恢复时间的快速全保护,且具有良好的扩展性。     

基于k 最短路由的mesh光网络p圈构造方法*

Pcycle是mesh光网络中一种十分优秀的保护算法,圈构造算法是p圈法设计的前提。首先介绍了圈的概念及常见圈构造算法和基于k最短路由的p圈启发式算法,提出了基于k最短路改进metaDijkstra的圈构造算法。实验仿真表明该方案比较适合网状光网络中的圈构造。     

Packet routing and selection on the POPS network

Partitioned optical passive stars (POPS) network has been proposed recently as a desirable model of parallel computing. Many papers have been published that address fundamental problems on these networks. Packet routing is one such important problem. We present a randomized algorithm in this paper that performs better than the best prior algorithms. We also present a randomized algorithm for selection on the POPS network.     

一种基于IP网络的QoS约束组播路由算法

针对时延约束最小代价组播路由问题,结合禁忌搜索算法和模拟退火算法的优点,提出了一种改进的混合遗传路由算法TSSAGMA。通过分析与仿真,证实了该算法在解决时延约束最小代价组播路由的问题上优于传统算法,能够在较小的代价下搜索到较好的解。     

Design and implementation of a random neural network routing engine

Random neural network (RNN) is an analytically tractable spiked neural network model that has been implemented in software for a wide range of applications for over a decade. This paper presents the hardware implementation of the RNN model. Recently, cognitive packet networks (CPN) is proposed as an alternative packet network architecture where there is no routing table, instead the RNN based reinforcement learning is used to route packets. Particularly, we describe implementation details for the RNN based routing engine of a CPN network processor chip: the smart packet processor (SPP). The SPP is a dual port device that stores, modifies, and interprets the defining characteristics of multiple RNN models. In addition to hardware design improvements over the software implementation such as the dual access memory, output calculation step, and reduced output calculation module, this paper introduces a major modification to the reinforcement learning algorithm used in the original CPN specification such that the number of weight terms are reduced from 2n/sup 2/ to 2n. This not only yields significant memory savings, but it also simplifies the calculations for the steady state probabilities (neuron outputs in RNN). Simulations have been conducted to confirm the proper functionality for the isolated SPP design as well as for the multiple SPP's in a networked environment.     

带选择适应性的水下传感器网络分布式路由算法

针对水下传感器网络能量消耗大、延迟时间长、信道利用率低等问题,提出了一种带选择适应性的水下传感器网络分布式路由算法(AS-UWSN).AS-UWSN使数据包成为一种具有以最大阈值为能耗界限的选择性和具有以最大信息素浓度为搜索对象的适应性的蚁群,以当前链路的能量损耗、网络延迟、误包率作为信息素的产生因子,每次迭代时蚁群都会直接搜索最优的节点转发路径,迭代次数少且具有更好的实时性和灵活性.实验仿真结果表明,在水下无线传感器网络的能量优化以及延迟时间控制、信道利用率提升上采用AS-UWSN算法得到了较好的效果.     

面向移动汇聚节点的无线传感器网络自适应路由方法

针对无线传感器网络面向移动汇聚节点的自适应路由问题,为实现路由过程中对节点能量以及计算、存储、通信资源的优化利用,并对数据传输时延和投递率等服务质量进行优化,提出一种基于强化学习的自适应路由方法,设计综合的奖赏函数以实现对能量、时延和投递率等多个指标的综合优化。从报文结构、路由初始化、路径选择等方面对路由协议进行详细设计,采用汇聚节点声明以及周期性洪泛机制加速收敛速度,从而支持汇聚节点的快速移动。理论分析表明基于强化学习的路由方法具备收敛快、协议开销低以及存储计算需求小等特点,能够适用于能量和资源受限的传感器节点。在仿真平台中通过性能评估和对比分析验证了所述自适应路由算法的可行性和优越性。     

Multispikes and synchronization in a large neural network with temporal delays

Coherent rhythms in the gamma frequency range are ubiquitous in the nervous system and thought to be important in a variety of cognitive activities. Such rhythms are known to be able to synchronize with millisecond precision across distances with significant conduction delay; it is mysterious how this can operate in a setting in which cells receive many inputs over a range of time. Here we analyze a version of mechanism, previously proposed, that the synchronization in the CA1 region of the hippocampus depends on the firing of "doublets" by the interneurons. Using a network of local circuits that are arranged in a possibly disordered lattice, we determine the conditions on parameters for existence and stability of synchronous solutions in which the inhibitory interneurons fire single spikes, doublets, or triplets per cycle. We show that the synchronous solution is only marginally stable if the interneurons fire singlets. If they fire doublets, the synchronous state is asymptotically stable in a larger subset of parameter space than if they fire triplets. An unexpected finding is that a small amount of disorder in the lattice structure enlarges the parameter regime in which the doublet solution is stable. Synaptic noise reduces the regime in which the doublet configuration is stable, but only weakly.     

Shipment partitioning and routing to minimize makespan in a transportation network

This paper addresses the problem of partitioning and transporting a shipment of known size through an n-node public transportation network with known scheduled departure and arrival times and expected available capacities for each departure. The objective is to minimize the makespan of shipping. The problem while practical in its scope, has received very little attention in the literature perhaps because of the concentration of research in vehicle routing without regard to partitioning and partitioning without regard to routing. A general non-linear programming model is developed. The model is then converted into a linear model through the Routing First and Assignment Second approach. This approach is different from the general decomposition approaches since they normally do not guarantee optimality. However, the linear model still involves a large number of constraints, and solution is not attempted here. Instead, three heuristics are proposed for solving the problem. Two of the heuristics use iterative techniques to evaluate all possible paths. The third heuristic uses a max-flows approach based upon aggregated capacities to reduce the size of the network presented to the other heuristics. This allows for a good starting point for other heuristics, and may impact the total computational effort. We find that the heuristics developed perform well because in the case of networks that are not congested, they find the optimal solution.     

群智能在Ad Hoc网络QoS组播路由中应用的研究

通过对Ad Hoc网络QoS组播路由问题的深入研究,提出了一种融合量子粒子群优化和蚁群优化的群智能混合算法(QPSOACO算法)。该算法融合QPSO思想以加速蚁群算法在路由发现及维护时的收敛速度,进一步提高算法对网络节点移动性的适应能力。仿真实验表明,该算法对Ad Hoc网络环境的适应性良好。