小世界网络模型下的无线传感器网络

复杂网络是具有复杂拓扑结构和动力学行为特征的大规模网络,无线传感器网络呈现出多种复杂网络特性,如多跳、自组织特性等,这表明可借助复杂网络理论研究无线传感器网络的拓扑结构和动力学特性。在无线传感器网络的复杂网络特征的基础上建立小世界网络模型。仿真表明小世界网络模型下的无线传感器网络符合小世界网络具备的性质。     

基于一种新的多重权重复杂网络模型的自适应同步研究

在传统的单权复杂网络建模方法的基础上,建立一种新的多重权重复杂网络模型。根据不同性质的权重,通过网络拆分的思想,将多重权重复杂网络拆分为几个性质不同的子网络。进而研究具有多重权重复杂网络的全局自适应同步,给出网络自适应同步的一般条件。最后以Lorenz系统为例,验证该方法的有效性。     

利用信任支持度构建客户信任网络

利用信任的社会性质进行信任传递,可有效缓解数据稀疏的问题,提高推荐系统的覆盖率和准确率。目前对信任网络的研究存在信任模型建立不准确、信任传递机制复杂与失真等问题。为准确表述信任网络中的客户信任关系,引入信任支持度的概念,提出了一种信任度与信任支持度相结合的客户信任模型;制定了符合信任社会性的传递规则,构建了基于该模型的客户信任网络,并设计了相应的个性化推荐算法。实验结果表明,此模型提高了推荐系统的覆盖率、准确率及推荐质量。     

服务社区的无标度性质研究

文章揭示了基于UDDI注册中心的增长性服务社区网络社团结构性质,并从服务注册拓扑结构来研究与总结服务社区网络的无标度性质。因此本文关于无标度服务社区网络的研究为面向服务的体系结构提供有力的理论与实践依据,也对复杂网络的理论与实证研究起到了一定的推动作用。     

基于加权网络的客户需求聚类方法

针对高端制造业客户需求数据庞大、需求间相关关系复杂的问题,提出了基于加权网络的客户需求聚类方法。将客户需求看做加权网络的节点,将客户需求之间的相关关系看做加权网络的边,构建客户需求的加权网络,并在加权网络的基础上结合聚类算法对客户需求进行聚类处理,从而将杂乱无章的客户需求根据相关程度进行分类。考虑到需求之间关系的主观性和模糊性,采用三角模糊数来量化加权网络的边权,最后以客户对塔式起重机的需求为例对所提出方法的有效性进行了验证。     

复杂网络的社区发现算法研究

复杂网络是对于复杂系统的高度抽象,其中许多性质如小世界性质、无标度性质以及聚集性质等等已经得到了充分的研究。大量文献表明,复杂网络呈现出的社区结构特性。如何在大型网络中高效地发现社区问题是近年来复杂网络的研究热点。文章讨论了一些关于社区发现方面的概念、理论、算法及应用等,并简述了其发展趋势。     

基于复杂网络理论的计算机网络拓扑分析

复杂网络是指具有无标度、小世界、吸引子、自相似、自组织中部分或者所有性质的网络。在现实世界中,许多复杂的系统基本上都能以网络来进行描述,而现实中的那些复杂的系统则可以以“复杂网络”来称之,比如社会网、交通网、电力网、万维网、因特网等等都可以称之为复杂网络。本文主要通过对复杂网络理论的介绍,从而对计算机Intemet网进行分析,对Intemet网这一复杂系统进行探究,揭示Intemet拓扑现象的特性、规律及动因。     

车联网建模和统计性质分析及其路由策略综述

利用复杂网络理论和方法对通信网络进行建模、分析网络演化过程中的统计性质,进而指导路由策略优化,已经成为热点领域。分析了车联网建模、车联网统计性质分析、车联网路由策略优化,以及车联网路由协议设计等方面的研究现状,并提出从三个方面进行改进,分别是:采用有向加权图来描述车联网的拓扑结构;从车联网与移动自组织网络的统计性质差异入手,寻找影响车联网传输能力的关键统计性质;利用复杂网络,研究基于多输入多输出技术的多径路由(即同时利用多个信道、多条路径传输)优化策略。     

亲属关系网络统计特性研究

近年来,许多学者以复杂网络为主要的研究工具,开始深入研究社会网络、技术网络、生物网络和神经网络四大类网络以及各个网络的统计特性和网络上的动力学行为。亲属关系作为一种复杂的社会关系,不同于已有的复杂网络中节点间的连接关系,基于亲属关系构造的复杂网络有其独特的性质。以亲属关系为连接边构建一定地区范围内的亲属关系网络,在此基础上分析和研究亲属关系网络拓扑结构具有的普遍复杂网络统计特性。研究指出,亲属关系网络的拓扑结构具有小世界效应、独特的度概率分布和度-度正相关等特征。同时,对于亲属关系网络的研究将有助于分析出某地区近亲结婚现象存在的可能性高低。     

复杂网络上的非线性负载容量模型

对网络的形成机制、几何性质、演化规律以及网络结构分析、行为预测和控制的研究产生了复杂网络学科,其中关于复杂网络级联失效过程的研究一直受到研究人员的关注.文中提出一种更符合实际网络的两变量非线性负载容量模型来解决复杂网络的级联失效问题.通过在4个不同的网络上进行仿真,验证了所提模型的有效性,发现该模型能够更好地抵御级联失效.实验还发现,所提模型在获得较高鲁棒性的情况下具有更好的性能,且投资成本较小.     

基于复杂网络的电子商务群聚消费传播模型研究*

互联网的发展带来无限商机的同时,也通过网络平台日益拉近顾客之间的联系,研究群聚消费对企业的影响又是一个新的议题。本文利用某电子商务网站的顾客消费数据展开实证研究,发现电子商务顾客消费网络体现出复杂网络的典型特征。通过对该网络的项目度分布及群聚特征的深入研究,从复杂网络的视角重新审视了电子商务中顾客消费行为的群聚性。针对电子商务中顾客消费的群聚行为及忠诚顾客对顾客群体行为的影响提出一种假设模式,并构建了一个电子商务顾客消费网络的演化-传播-免疫计算机模型进行模拟验证,为研究电子商务企业中顾客群体行为提供了一个新的探索和尝试。     

Determination and exchange of supply information for co-operation in complex production networks

Today's manufacturing industry is characterised by strong interdependencies between companies operating in globally distributed production networks. The operation of such value-added chains has been enabled by recent developments in information and communication technologies (ICT) and computer networking. To gain competitive advantages and efficiency improvements such as reduced inventory and higher delivery reliability, companies are introducing information exchange systems that communicate demand to suppliers and production progress information to customers in the network. This article proposes a system that supports co-operation in complex production networks by enabling companies to determine and exchange supply information with their customers. The requirements for such a system are analysed and it is embedded in a framework of supply chain management business processes. The system facilitates the determination and exchange of meaningful, reliable and up-to-date order status information from the supplier to the customer. Based on comparing the progress of an internal production order with a pre-defined milestone model for each product, the status of the customer order is determined and—in case of lateness—communicated to the customer together with an early warning. To demonstrate the developed supply information concepts and processes, the business process is implemented as a pilot system and evaluated by the user companies participating in the 5th Framework IST project Co-OPERATE.     

Insensitivity in processor-sharing networks

We consider an open network of processor-sharing nodes with state-dependent service capacities, i.e., the speed of each node may depend on the number of customers at any node. We demonstrate that the stationary distribution of the network state is insensitive to the distribution of service times if and only if the service capacities are balanced, i.e., the considered network is a Whittle network. The stationary distribution then has a closed-form expression and the expected sojourn time of a customer at any node is proportional to its required quantity of service. These results are extended to the cases of closed networks and state-dependent arrival rates and routing. Two simple examples illustrate the practical interest of these results in the context of communication networks.     

G-Networks: Development of the Theory of Multiplicative Networks

This is a review on G-networks, which are the generalization of the Jackson and BCMP networks, for which the multi-dimensional stationary distribution of the network state probabilities is also represented in product form. The G-networks primarily differ from the Jackson and BCMP networks in that they additionally contain a flow of the so-called negative customers and/or triggers. Negative customers and triggers are not served. When a negative customer arrives at a network node, one or a batch of positive (ordinary) customers is killed (annihilated, displaced), whereas a trigger displaces a positive customer from the node to some other node. For applied mathematicians, G-networks are of great interest for extending the multiplicative theory of queueing networks and for practical specialists in modeling computing systems and networks and biophysical neural networks for solving pattern recognition and other problems.     

贝叶斯网模型在推荐系统中的应用研究

针对网上智能中推荐系统的个性化问题,提出了一种新的基于贝叶斯网模型的商品推荐方法,它包括贝叶斯网客户购物模型的建立和基于概率推理的推荐集的产生两个过程。实数据上的实验表明该方法是一种有效的能为不同客户产生准确而个性化的商品推荐方法。     

Decomposition of Queueing Networks with Dependent Service and Negative Customers

Queueing networks with negative customers (G-networks) and dependent service at different nodes are studied. Every customer arriving at the network is defined by a set of random parameters: his route over the network (a sequence of nodes visited by the customers), route length, and volume and service length of the customer at every stage of the route. For G-networks, which are the analogs of BCMP-networks, the multidimensional stationary distribution of the network state probabilities is shown to be representable in product form.     

Queueing Networks with Dynamic Routing and Dynamic Stochastic Bypass of Nodes

We consider open exponential networks with routing matrices that depend on a network state. A customer entering a node is either independently of other customers queued with probability that depends on the network state or instantly bypasses the node with complementary probability. After bypassing a node, customers are routed according to a stochastic matrix that depends on the network state and may differ from the routing matrix. Under certain restrictions on parameters of the model, we establish a sufficient ergodicity condition and find the final stationary distribution.     

NEVA: Visual Analytics to Identify Fraudulent Networks

Trust-ability, reputation, security and quality are the main concerns for public and private financial institutions. To detect fraudulent behaviour, several techniques are applied pursuing different goals. For well-defined problems, analytical methods are applicable to examine the history of customer transactions. However, fraudulent behaviour is constantly changing, which results in ill-defined problems. Furthermore, analysing the behaviour of individual customers is not sufficient to detect more complex structures such as networks of fraudulent actors. We propose NEVA (Network dEtection with Visual Analytics), a Visual Analytics exploration environment to support the analysis of customer networks in order to reduce false-negative and false-positive alarms of frauds. Multiple coordinated views allow for exploring complex relations and dependencies of the data. A guidance-enriched component for network pattern generation, detection and filtering support exploring and analysing the relationships of nodes on different levels of complexity. In six expert interviews, we illustrate the applicability and usability of NEVA.     

Queueing networks with mobile servers: The mean-field approach

We consider queueing networks which are made from servers exchanging their positions on a graph. When two servers exchange their positions, they take their customers with them. Each customer has a fixed destination. Customers use the network to reach their destinations, which is complicated by movements of the servers. We develop the general theory of such networks and establish the convergence of the symmetrized version of such a network to some nonlinear Markov process.     

Service integrators in business networks—the importance of relationship values

To realise the potentials of CRM (customer relationship management), relationship-specific processes need to be designed and implemented in companies. This is all the more important and complicated in business networks where two or more actors collaborate to serve the customers. A good collaboration within business networks is the basis for understanding the customer process and identifying customer needs. But, even in these days of customer orientation, transaction orientation is still a matter of strong interest, and the following questions remain to be answered: What is the difference between relationship-oriented processes and transaction-oriented processes, and how can relationship-oriented processes be designed for a business network? The authors give first answers to both questions by using a systematic, goal-oriented specialisation of generic actions. To give an example, one relationship-oriented process will be designed and specified for a certain customer process in the course of this paper.