基于半导体光放大器中非线性偏振旋转效应单一光缓存环全光时隙交换处理能力研究

对基于半导体光放大器(SOA)中非线性偏振旋转效应(NPR)效应的单一光缓存环多数据包的全光时隙交换(TSI)处理能力进行了理论和实验研究,在使用归纳法导出单一缓存环实现多数据包全光时隙(TSI)必要条件的基础上,针对各种全光TSI操作要求得出了相应光数据包的调度方案,在实验上,以基于SOA中NPR效应的单一光缓存环实验系统,开展了多数据包全光TSI操作的实验研究,根据上述光数据包理论调度方案进行相应系统参数设定,进行了速率为10 Gb/s的3个和4个数据包的全光TSI实验,实验结果与理论预期相符合,研究成果为减少昂贵SOA元件的用量、简化基于光缓存环全光TSI系统的结构提供了可靠依据,对推进全光TSI技术的发展具有重要意义。     

时隙光分组交换网络中一种新的光缓存优化配置方案

研究了时隙光分组交换网中的光缓存配置方案,针对反馈共享式缓存结构,通过对传统的连续分布式光缓存结构中不同延迟粒度的光缓存丢包的分布情况仿真结果研究,发现在传统的连续分布式光缓存结构中,丢包主要发生在小粒度的光缓存上,为此,提出通过适当增加小粒度的光缓存的方法,达到有效地降低丢包率,仿真结果显示,这种光缓存方案可以明显降低节点的丢包率.     

基于分组动态帧时隙的射频识别防碰撞算法

提出了动态调整帧长度原则和标签分组方法, 在此基础上结合二者设计了一种新型的分组动态帧时隙防碰撞算法, 首先对未识别的标签进行数量估计, 如果标签数量超过临界值, 则对标签进行分组, 通过动态调整识别帧长适应每组标签数量进行高效识别. 仿真结果表明: 系统吞吐率稳定在34.6%–36.8% 之间, 识别过程所需要的时隙数也保持了线性增加, 在待识别标签数量大于2000的情况下, 与传统的防碰撞算法相比, 时隙效率提高了30%以上, 极大优化了系统的吞吐率, 节约系统资源. 关键词： 防碰撞 分组 动态帧时隙 吞吐率     

一种高能效无线传感器网络MAC协议研究

为了解决无线传感器网络中MAC层空闲侦听、冲突和控制开销所带来的无效功耗等问题,提出了一种高能效无线传感器网络动态非等分时隙MAC新方法;该方法依据网络拓扑和监测类型分析了覆盖率模型,设计了通过选举最低剩余能量节点为休眠节点的动态选举算法,推导得到了非等分配时隙协议的算法公式,同时,采用簇内单向广播的时钟同步算法保证了网络节点拥有相同的时间基准;在无线传感器测试床上进行仿真对比实验,结果表明该方法较好地实现了动态调节工作节点数量和非等分传输时隙的协议功能,MAC层的能量有效性显著提高;该方法可有效使用网络能量,延长网络生命周期,是一种高能效的无线传感器网络MAC协议。     

基于云计算Hadoop异构集群的并行作业调度算法

针对Hadoop异构集群中计算和数据资源的不一致分布所导致的调度性能较低的缺点,设计了一种基于Hadoop集群和改进Late算法的并行作业调度算法;首先,介绍了基于Hadoop框架和Map-Reduce模型的调度原理,然后,在经典的Late调度算法的基础上,对Map任务和Reduce任务的各阶段执行时间进度比例进行存储和更新,为了进一步地提高调度效率,将慢任务迁移到本地化节点或离数据资源较近的物理节点上,并给了基于改进Late算法的作业调度流程;为了验证文中方法,在Hadoop集群系统上测试,设定1个为Jobtracker主控节点和7个为TaskTracker节点,实验结果表明文中方法能实现异构集群的作业调度,且与其它方法比较,具有较低的预测误差和较高的调度效率。     

串行级联脉冲位置调制码辅助的时隙同步技术

针对深空光脉冲位置调制(PPM)通信,基于最大期望(EM)定时误差估计原理,研究了一种基于串行级联脉冲位置调制(SCPPM)码辅助的光PPM时隙同步的解决方案。由于标准的SCPPM译码方法无法获得EM估计时所需的期望值,因此提出一种将SCPPM译码输出的软信息转换为PPM各时隙期望值的方法。由SCPPM译码输出先进行硬判决,再通过累加模块获得累加器状态;根据该状态选择下一个PPM映射方式,进而获得各PPM时隙的概率及期望;最后利用EM算法预测时钟偏差值从而获得最佳采样点。仿真结果表明,对于2倍PPM时隙频率的异步采样信号,当时钟误差在-0.5~0.5个PPM时隙范围内时,此方法能有效实现PPM时隙同步。     

基于Wi-Fi与Web的云计算资源调度算法研究

为了缩短云计算执行时间,改善云计算性能,在一定程度上加强云计算资源节点完成任务成功率,需要对云计算资源进行调度。当前的云计算资源调度算法在进行调度时,通过选择合适的调度参数并利用CloudSim仿真工具,完成对云计算资源的调度。该算法在运行时有效地进行平衡负载,导致云计算资源调度的均衡性能较差,存在云计算资源调度结果误差大的问题。为此,提出一种基于Wi-Fi与Web的云计算资源调度算法。该算法首先利用自适应级联滤波算法对云计算资源数据流进行滤波降噪,然后以降噪结果为基础,采用本体论对云计算资源进行预处理操作,最后通过人工蜂群算法完成对云计算资源的调度。实验结果证明,所提算法可以良好地应用于云计算资源调度中,有效提高了云计算资源利用率,具有实用性以及可实践性,为该领域的后续研究发展提供了可靠支撑。     

弹性分组环异步网络的同步传输机制

介绍了弹性分组环异步网络中发送速率同步功能的特点和实现同步的方式.结合弹性分组环环网中的带宽分配原则提出了一种能够适用于弹性分组环异步环网的同步传输机制：动态加权发送速率.该机制依据节点主传送队列深度动态改变接收数据流的转发权值来实现同步传输.研究结果表明该机制能够实现弹性分组环异步环网中的同步传输,节点主传送队列不会溢出.     

基于关键路径链和PACGA的网络总线资源调度方法研究

针对传统工业控制网络总线资源调度算法在节点数量逐渐增加时收敛速度慢和搜索精度不高,且准确度及效率低等问题, 提出了一种基于关键路径链和多态蚁群遗传算法(PACGA)的资源调度方法,采用关键路径链的调度算法获取需求调度的节点,不同节点间采用多态蚁群遗传算法进行资源的调度,依据照工业控制网络资源调度的特征,用自适应调整挥发系数增强节点的全局搜索性能,通过候选节点集方法缩小搜索区域提高算法的搜索效率,完成工业控制网络总线资源的高效调度。仿真实验说明,该种方法在工业控制过程中任务数量较多的情况下仍然具备较高的运行效率和精度,并且具有较低的运行时间,具有较强的应用价值。     

基于TDMA的星间链路时隙分配设计与仿真评估

基于TDMA的星间链路体制组网灵活,传输效率高,已成为今后星间链路的一种发展趋势。对于TDMA的星座网络而言,其时隙分配是影响业务时延的重要因素,本文就一种双层混合型星座提出了一种时隙分配方案,并对星座网络的传输进行了仿真,分别从广播和单播两种业务的角度针对星间链路传输性能的时延指标进行了评估分析。     

The importance of centralities in dark network value chains

This paper introduces three novel centrality measures based on the nodes’ role in the operation of a joint task, i.e., their position in a criminal network value chain. For this, we consider networks where nodes have attributes describing their “capabilities” or “colors”, i.e., the possible roles they may play in a value chain. A value chain here is understood as a series of tasks to be performed in a specific order, each requiring a specific capability. The first centrality notion measures how many value chain instances a given node participates in. The other two assess the costs of replacing a node in the value chain in case the given node is no longer available to perform the task. The first of them considers the direct distance (shortest path length) between the node in question and its nearest replacement, while the second evaluates the actual replacement process, assuming that preceding and following nodes in the network should each be able to find and contact the replacement. In this report, we demonstrate the properties of the new centrality measures using a few toy examples and compare them to classic centralities, such as betweenness, closeness and degree centrality. We also apply the new measures to randomly colored empirical networks. We find that the newly introduced centralities differ sufficiently from the classic measures, pointing towards different aspects of the network. Our results also pinpoint the difference between having a replacement node in the network and being able to find one. This is the reason why “introduction distance” often has a noticeable correlation with betweenness. Our studies show that projecting value chains over networks may significantly alter the nodes’ perceived importance. These insights might have important implications for the way law enforcement or intelligence agencies look at the effectiveness of dark network disruption strategies over time.     

Fairness and throughput performance of infrastructure IEEE 802.11 networks with hidden-nodes

The fairness behavior and throughput performance of IEEE 802.11 distributed coordination function and request-to-send/clear-to-send channel access scheme in the presence of hidden nodes are investigated. A mathematical model which accurately predicts a user’s throughput performance and packet collision probability in non-saturated traffic and asymmetric hidden node environments is developed. The model allows us to see many interesting results in networks with hidden nodes. In an asymmetric hidden node network environment, the network fairness performance depends on the traffic load. In low traffic conditions, users get their fair share of the resources. However, in moderate-to-high traffic conditions, users that experience less number of hidden nodes dominate the network, causing badly located stations in a network to starve. In addition, the performance of request-to-send/clear-to-send channel access scheme, which is developed as a solution to hidden node problem, in networks with hidden nodes, is also estimated. It is shown that request-to-send/clear-to-send contention resolution scheme greatly improves the network fairness performance in hidden node scenarios. The developed model enables us to more accurately estimate the performance of practical wireless local area networks, where hidden node occurrence is common. Theoretical analysis presented in the paper is validated with simulation results.     

利用邻域“结构洞”寻找社会网络中最具影响力节点

识别复杂网络中的关键节点对网络结构优化和鲁棒性增强具有十分重要的意义. 经典的关键节点测量方法在一定程度上能够辨识网络中影响力节点, 但存在一定局限性: 局部中心性测量方法仅考虑节点邻居的数目, 忽略了邻居间的拓扑关系, 不能在计算中反映邻居节点间的相互作用; 全局测量方法则由于算法本身的复杂性而不能应用于大规模社会网络的分析, 另外, 经典的关键节点测量方法也没有考虑社会网络特有的社区特征. 为高效、准确地辨识具有社区结构的社会网络中最具影响力节点, 提出了一种基于节点及其邻域结构洞的局部中心性测量方法, 该方法综合考虑了节点的邻居数量及其与邻居间的拓扑结构, 在节点约束系数的计算中同时体现了节点的度属性和“桥接”属性. 利用SIR(易感-感染-免疫)模型在真实社会网络数据上对节点传播能力进行评价后发现, 所提方法可以准确地评价节点的传播能力且具有强的鲁棒性.     

中国铁路客运网网络性质的研究

中国铁路客运系统可以采用两种不同的网络构建方式来描述. 一种是以铁路的站点作为“节点”，并以轨道作为“边”，这样生成的网络称为铁路地理网. 统计显示该网络的平均群聚系数〈C〉近似为零，故该网络为树状网络. 另一种是以站点作为“节点”，任意两个站点间只要有同一列车在这两个站点停靠，就可以认为这两个站点间有连线，这样生成的网络称为车流网. 统计显示该网络有较大的平均群聚系数和较小的平均网络距离〈d〉，而且该网络节点的度分布基本上服从无标度幂律分布，故车流网为具有无标度性质的小世界网络. 关键词： 铁路地理网 车流网 小世界 无标度分布     

The gateway coefficient: a novel metric for identifying critical connections in modular networks

The modular structure of a complex network is an important and well-studied topological property. Within this modular framework, particular nodes which play key roles have been previously identified based on the node’s degree, and on the node’s participation coefficient, a measure of the diversity of a node’s intermodular connections. In this contribution, we develop a generalization of the participation coefficient, called the gateway coefficient, which measures not only the diversity of the intermodular connections, but also how critical these connections are to intermodular connectivity; in brief, nodes which form rare or unique “gateways” between sparsely connected modules rank highly in this measure. We illustrate the use of the gateway coefficient with simulated networks with defined modular structure, as well as networks obtained from air transportation data and functional neuroimaging.     

Small World Properties Generated by a New Algorithm Under Same Degree of All Nodes

Based on the model of the same degree of all nodes we proposed before, a new algorithm, the so-called “spread all over vertices” (SAV) algorithm, is proposed for generating small-world properties from a regular ring lattices. During randomly rewiring connections the SAV is used to keep the unchanged number of links. Comparing the SAV algorithm with the Watts-Strogatz model and the “spread all over boundaries” algorithm, three methods can have the same topological properties of the small world networks. These results offer diverse formation of small world networks. It is helpful to the research of some applications for dynamics of mutual oscillator inside nodes and interacting automata associated with networks.     

High Speed All-Optical Data Distribution Network

This article describes the performance and capabilities of an all-optical network featuring low latency, high speed file transfer between serially connected optical nodes. A basic component of the network is a network interface card (NIC) implemented through a unique planar lightwave circuit (PLC) that performs add/drop data and optical signal amplification. The network uses a linear bus topology with nodes in a “T” configuration, as described in the text. The signal is sent optically (hence, no latency) to all nodes via wavelength division multiplexing (WDM), with each node receiver tuned to wavelength of choice via an optical de-multiplexer. Each “T” node routes a portion of the signal to/from the bus through optical couplers, embedded in the network interface card (NIC), to each of the 1 through n computers.     

Constraints and entropy in a model of network evolution

Barabási–Albert’s “Scale Free” model is the starting point for much of the accepted theory of the evolution of real world communication networks. Careful comparison of the theory with a wide range of real world networks, however, indicates that the model is in some cases, only a rough approximation to the dynamical evolution of real networks. In particular, the exponent γ of the power law distribution of degree is predicted by the model to be exactly 3, whereas in a number of real world networks it has values between 1.2 and 2.9. In addition, the degree distributions of real networks exhibit cut offs at high node degree, which indicates the existence of maximal node degrees for these networks. In this paper we propose a simple extension to the “Scale Free” model, which offers better agreement with the experimental data. This improvement is satisfying, but the model still does not explain why the attachment probabilities should favor high degree nodes, or indeed how constraints arrive in non-physical networks. Using recent advances in the analysis of the entropy of graphs at the node level we propose a first principles derivation for the “Scale Free” and “constraints” model from thermodynamic principles, and demonstrate that both preferential attachment and constraints could arise as a natural consequence of the second law of thermodynamics.     

Scaling of mean first-passage time as efficiency measure of nodes sending information on scale-free Koch networks

Random walks on complex networks, especially scale-free networks, have attracted considerable interest in the past few years. A lot of previous work showed that the average receiving time (ART), i.e., the average of mean first-passage time (MFPT) for random walks to a given hub node (node with maximum degree) averaged over all starting points in scale-free small-world networks exhibits a sublinear or linear dependence on network order N (number of nodes), which indicates that hub nodes are very efficient in receiving information if one looks upon the random walker as an information messenger. Thus far, the efficiency of a hub node sending information on scale-free small-world networks has not been addressed yet. In this paper, we study random walks on the class of Koch networks with scale-free behavior and small-world effect. We derive some basic properties for random walks on the Koch network family, based on which we calculate analytically the average sending time (AST) defined as the average of MFPTs from a hub node to all other nodes, excluding the hub itself. The obtained closed-form expression displays that in large networks the AST grows with network order as N ln N, which is larger than the linear scaling of ART to the hub from other nodes. On the other hand, we also address the case with the information sender distributed uniformly among the Koch networks, and derive analytically the global mean first-passage time, namely, the average of MFPTs between all couples of nodes, the leading scaling of which is identical to that of AST. From the obtained results, we present that although hub nodes are more efficient for receiving information than other nodes, they display a qualitatively similar speed for sending information as non-hub nodes. Moreover, we show that that AST from a starting point (sender) to all possible targets is not sensitively affected by the sender’s location. The present findings are helpful for better understanding random walks performed on scale-free small-world networks.     

Sensitivity of the resilience of congested random networks to rolloff and offset in truncated power-law degree distributions

Random networks were generated with the random configuration model with prescribed truncated power-law degree distributions, parameterized by an exponent, an offset, and an exponential rolloff. As a model of an attack, each network had exactly one of its highest degree nodes removed, with the result that in some cases, one or more remaining nodes became congested with the reassignment of the load. The congested nodes were then removed, and the “cascade failure” process continued until all nodes were uncongested. The ratio of the number of nodes of the largest remaining cluster to the number of nodes in the original network was taken to be a measure of the network's resiliency to highest-degree node removal. We found that the resiliency is sensitive to both rolloff and offset (but not to cutoff) in the degree distribution, and that rolloff tends to decrease resiliency while offset tends to increase it.