基于节点动态连接度的网络社团划分算法

首先定义了节点动态连接度这一概念,然后介绍了基于节点动态连接度的网络社团划分算法,之后再对其中相关参数的取值范围和社团划分结果之间的关系进行了分析,并以Zachary网络为例验证了分析结论。在此基础上,以dolphins、polbooks和football 3个实际网络为对象,进行了社团划分实验,证明了本算法可通过动态调整参数实现对不同网络的社团划分。最后将实验结果与其他几种常见的社团划分算法结果进行了比较,证明了算法的优势,并对算法中需要注意的一些问题进行了说明。

基于节点电气耦合连接度的配电网启发式孤岛划分

分布式电源(DG)供电能力和周围负荷需求需要进行功率匹配,以保证故障后孤岛划分区域供电的稳定性和良好的电能质量。通过采集配电网中的量测终端数据,在研究基于单元融合法的配电网孤岛划分的基础上,提出利用节点电气耦合连接度指标筛选重要负荷节点,使得关键负荷单元能够得到优先融合,在较短的时间内,制定出孤岛划分的最优方案。仿真数据表明计及节点电气耦合连接度的配电网孤岛划分算法能够较为有效地融合配电网中一些关键节点,使配电网故障后,能够借助分布式电源的供电能力为非故障区域的负荷提供持续的供电服务。

电力通信网络节点关键度评估方法

由于电力通信网络的复杂性,对网络节点关键度的评估准确性较低,为此,本文提出电力通信网络节点关键度的评估方法,在引入节点增长速度和节点连接优先度参量的基础上,构建了电力通信网络拓扑模型,从节点影响范围及作用强度两个角度对节点属性进行计算,并带入模型中,实现了对节点关键度的评估。测试结果表明,本文设计的方法可以实现对不同规模网络环境节点关键度的准确评估,与对比方法相比具有明显优势。

深度神经网络的网络高敏感信息预警算法

针对传统的敏感信息预警算法因难以有效聚类信息而导致预警效果较差的问题,给出了一种新的敏感信息预警算法。首先,采集网络高词频中的敏感信息,其次,通过设置合理阈值完成对高敏感信息的准确挖掘,再次,通过深度神经网络对高敏感信息展开有效聚类,构建邻接矩阵,最后,计算网络参数节点的连接平均度,结合上述聚类结果实现对高敏感信息监测和预警。实验发现,应用传统算法的网络节点发送的数据不具有规律性,且预警响应耗时均在2 s以上,而应用深度神经网络算法的网络数据呈现出全连接状态,敏感信息可表现出高度的一致性,且该算法对该敏感信息的预警响应可在1 s内完成。研究表明,基于深度神经网络的预警算法可以应用在网络安全领域。

一种适用于Ad Hoc K重组播网络的负载均衡路由算法

Ad Hoc网络是一个多跳的无基础设施网络,本文在分析Ad Hoc网络自身特点的基础上,引入了一种多组播业务并存的K重组播网络,这种网络相对传统的组播网络具有节省系统开销,降低能量消耗的优点.文中对K重组播网络中的节点连接度的不同变化情况进行了理论上的详细研究,并在此基础上设计了一种适用于K重组播网络的负载均衡路由算法.仿真结果表明该路由算法拥塞控制性能良好,并能显著提高组播业务的稳定性.本文提出的这种K重组播网络能够广泛的应用于许多实际通信场合.

适用于自组织多重组播网络的均衡算法研究

在分析自组织网络自身特点的基础上,介绍一种多组播业务并存的多重组播网络,该网络相对传统的组播网络具有节省系统开销,降低能量消耗的优点,尤其适于铁路通信的应用。文中对多重组播网络中的节点连接度的不同变化情况进行了研究,并在充分考虑移动节点的实际通信能力基础上设计了一种适用于多重组播网络的负载均衡路由算法。算法非常适用于本文所提出的多重组播网络环境,与其它组播协议相比,能够在动态环境下以较高的成功率建立组播树,保持较高的数据包发送成功率。同时,该算法引入负载均衡机制后有效的平衡了各节点之间的负荷,消除了节点载荷突发的现象。仿真结果表明,该路由算法负载均衡性能良好,并能显著提高组播业务的稳定性。文章结尾对今后的研究工作进行了总结和展望。

Modeling and Robustness of Knowledge Network in Supply Chain

The growth and evolution of the knowledge network in supply chain can be characterized by dynamic growth clustering and non-homogeneous degree distribution.The networks with the above characteristics are also known as scale-free networks.In this paper,the knowledge network model in supply chain is established,in which the preferential attachment mechanism based on the node strength is adopted to simulate the growth and evolution of the network.The nodes in the network have a certain preference in the choice of a knowledge partner.On the basis of the network model,the robustness of the three network models based on different preferential attachment strategies is investigated.The robustness is also referred to as tolerances when the nodes are subjected to random destruction and malicious damage.The simulation results of this study show that the improved network has higher connectivity and stability.

Available capacity and robust wireless mesh connectivity of TDD-based networks

This paper addresses the available capacity and robust connectivity of time division duplex based wireless mesh networks （TDD-based WMNs）. A stochastic model is presented for TDD-based WMNs. Considering the parameters that affect the network performance like ratio of control slots number to data slots number, collision probability, node density and average hopcounts, the availa- ble capacity for each node is inferred. Meanwhile, the order of transmission range for robust connec- tivity of large scale WMNs is derived. With the stochastic model and inferred available capacity per node, the performance of TDD-based WMNs using IEEE 802.16 standard is analyzed under various conditions. Simulation results indicate that the available capacity of IEEE 802.16-based TDD-based WMNs and the theoretical result have the same increasing and decreasing trend as the node density increases. Simulation results also illustrate the optimal value of the ratio of control slots number to data slots number that maximizes the available capacity.

Guaranteed Rendezvous Algorithms for Cognitive Radio Networks

Rendezvous is a blind process establishing a communication link on a common channel between a pair of nodes in cognitive radio networks. We propose two guaranteed rendezvous algorithms for cognitive radio networks under both single-radio and multi-radio scenarios with an asynchronous setting. For single-radio scenario, each cycle length is a prime number associated with a channel hopping sequence.The rendezvous can be guaranteed as long as the IDs of the two nodes are different. For multi-radio scenario, we propose a cycle length and rotation based rendezvous algorithm. Each node generates a channel hopping sequence with only one cycle length. Then these radios of each nodes rotate on the generated sequence with different rotation numbers at each hopping cycle. The rendezvous between two nodes is guaranteed as long as they have different cycle lengths or the same cycle length with different number of rotations. We conduct simulations on three metrics and the results show that the proposed algorithms outperform the existing ones.

Pathway Hunter Tool在代谢途径分析中的应用

随着重建的基因组规模代谢网络越来越多,自动化的生物化学途径分析方法显得越来越重要,已经有多种基于此的途径分析工具开发出来了。其中,Pathway Hunter Tool(PHT)是主要用于分析代谢网络的最短路径、代谢物和酶负载点和瓶颈.以及计算相关统计学数据(如平均路径长度、平均节点连接度等)的工具。本文首先简介PHT,随后用它分析E.coli K-12 MG1655代谢网络中a-D-葡萄糖和丙酮酸之间的最短路径及其代谢网络的瓶颈,最后计算4种典型生物的平均路径长度、平均节点连接度以及它们代谢网络中节点连接度最高的10种代谢物。结果表明它的分析与计算快速、准确,加之其用户界面友好、便于操作,因此可以作为代谢途径分析的强有力工具。

Modeling Dynamic Evolution of Online Friendship Network

In this paper,we study the dynamic evolution of friendship network in SNS(Social Networking Site).Our analysis suggests that an individual joining a community depends not only on the number of friends he or she has within the community,but also on the friendship network generated by those friends.In addition,we propose a model which is based on two processes:first,connecting nearest neighbors;second,strength driven attachment mechanism.The model reflects two facts:first,in the social network it is a universal phenomenon that two nodes are connected when they have at least one common neighbor;second,new nodes connect more likely to nodes which have larger weights and interactions,a phenomenon called strength driven attachment(also called weight driven attachment).From the simulation results,we find that degree distribution P(k),strength distribution P(s),and degree-strength correlation are all consistent with empirical data.