主动网络技术综述

Internet的迅速发展和用户需求的不断增长,使得Internet上新业务的提供成为瓶颈。主动网络的目的是让网络有计算能力,使得灵活加载新业务成为可能,这为Internet的发展开辟了新的方向。文章首先介绍了主动网络的概念与意义,然后给出了主动节点的结构以及密封囊的传输、加载和执行机制,介绍了国内外研究动态与进展。最后提出主动网络的一个实际应用。     

Particle swarm optimization-based DRWA for wavelength continuous WDM optical networks using a novel fitness function

Greater demand of bandwidth and network usage flexibility from customers along with new automated means for network resource management has led to the concept of dynamic resource provisioning in WDM optical networks where unlike the traditional static channel assignment process, network resources can be assigned dynamically. This paper examines a novel particle swarm optimization (PSO)-based scheme to solve dynamic routing and wavelength assignment (dynamic RWA) process needed to provision optical channels for wavelength continuous Wavelength Division Multiplexed (WDM) optical network without any wavelength conversion capability. The proposed PSO scheme employs a novel fitness function which is used during quantization of solutions represented by respective particles of the swarm. The proposed fitness function takes into account the normalized path length of the chosen route and the normalized number of free wavelengths available over the whole route, enabling the PSO-based scheme to be self-tuning by minimizing the need to have a dynamic algorithmic parameter ‘α’ needed for better performance in terms of blocking probability of the connection requests. Simulation results show better performance of the proposed PSO scheme employing novel fitness function for solving dynamic RWA problem, not only in terms of connection blocking probability but also route computation time as compared to other evolutionary schemes like genetic algorithms.     

Rich club characteristics of dynamic brain functional networks in resting state

Conventional brain functional networks are constructed by extracting the entire time series from functional Magnetic Resonance Imaging (fMRI). Yet such a method is easy to ignore the dynamic interaction patterns of brain regions that essentially change across time. In this study, we analyze the functional connectivity characteristics of Rich Club in resting-state brain functional networks, and study the dynamic functional differences of core brain regions at different time periods. First, the time series is extracted from resting-state fMRI to construct a dynamic brain functional network. Then, Rich Clubs of different time periods are determined by the Rich Club coefficients. In particular, the efficiency of each Rich Club is calculated to examine the influences of the Rich Connections, Feeder Connections and Local Connections. Finally, the node degree, clustering coefficient and efficiency for Rich Club nodes are calculated to quantify the dynamic processes of Rich Clubs, and the functional connectivity of Rich Clubs are compared with those of the functional networks constructed by the entire fMRI time series. Experimental results demonstrate that the distribution of Rich Clubs in the dynamic brain functional network is consistent with that from the entire fMRI time series, while the composition and functional connectivity of Rich Club dynamically change across time. Moreover, Rich connection and Local connection in the brain functional networks show a significant correlation with the efficiency of Rich Club, and the local and the global efficiency of Rich Clubs are greater than that of the global network. These results further illustrate the viewpoint that Rich Clubs have significant influence on the functional characteristics of global brain functional networks.

     

What kind of intimacy is meaningful to you? How intimate interactions foster individuals' sensemaking of innovation

This study examines how intimacy affects individuals' sensemaking of innovation in their organization. Although sensemaking facilitates understanding innovation and envisioning new worldviews, it involves a delicate process of self-disclosure, reflection, personal contact and communication. Intimacy focuses on time-bounded interactions that foster individuals' progressive self-disclosure and perceptions of mutual understanding. Therefore, drawing on intimacy theories, we investigate from a microlevel perspective how temporally bounded intimate interactions foster the meaningfulness of innovation for individuals. As sensemaking processes differ in large-scale radical and incremental innovations, we examine both contexts in a post hoc analysis. Through a field study, we show that different intimacy dynamics (emotional, cognitive and listening) influence meaningfulness perceptions. In particular, we find that the emotional intimacy dynamics positively influence meaningfulness perceptions in the context of radical innovation initiatives, while the cognitive and listening intimacy dynamics positively influence meaningfulness perceptions in the context of incremental innovation initiatives. This study contributes to the sensemaking innovation literature by introducing intimacy as an enabler of sensemaking. Our study also suggests that managers should encourage moments of intimate interaction when pursuing innovation to facilitate sensemaking of change.     

A Dynamic Transportation Model for the Stockholm Area: Implementation Issues Regarding Departure Time Choice and OD-pair Reduction

Road traffic congestion is an increasing problem in urban areas. Building new roads often attracts latent demand and turns parts of the city into building sites for several years. Policy measures that stimulate more effective use of the existing network, such as variable road pricing, are therefore becoming increasingly popular among policy makers and citizens. These measures are often aimed at changing the temporal distribution of traffic. Yet transportation models taking departure time choice into account are rare. This paper describes the implementation of an urban transportation application for Stockholm, which includes departure time choice, mode choice and time dependent network assignment. Through iterations between demand and supply the objective of the transportation model is to forecast effects of congestion charges, intelligent transport systems and infrastructure investments on departure time choice. The complexity of large-scale departure time choice modelling and dynamic traffic assignment is high, which results in very long run times. Therefore, research on how to increase model efficiency is needed. This paper describes choices made in the implementation for a more efficient model.     

Force-Based Incremental Algorithm for Mining Community Structure in Dynamic Network

Community structure is an important property of network. Being able to identify communities can provide invaluable help in exploiting and understanding both social and non-social networks. Several algorithms have been developed up till now. However, all these algorithms can work well only with small or moderate networks with vertexes of order 104. Besides, all the existing algorithms are off-line and cannot work well with highly dynamic networks such as web, in which web pages are updated frequently. When an already clustered network is updated, the entire network including original and incremental parts has to be recalculated, even though only slight changes are involved. To address this problem, an incremental algorithm is proposed, which allows for mining community structure in large-scale and dynamic networks. Based on the community structure detected previously, the algorithm takes little time to reclassify the entire network including both the original and incremental parts. Furthermore, the algorithm is faster than most of the existing algorithms such as Girvan and Newman＇s algorithm and its improved versions. Also, the algorithm can help to visualize these community structures in network and provide a new approach to research on the evolving process of dynamic networks.     

Dynamic call and connection admission control in automatically switched optical network for grid computing applications

In recent years,Grid computing applications are becoming more and more important to the scientific and business communities and are likely to open to the consumer market and widely develop in the near future,which is a great challenge brought by the potentially large number of Grid users(perhaps millions)and high frequency of their job requests.Automatically switched optical network(ASON),which is a promising high capacity intelligent transport network infrastructure,has been already deployed in the world and regarded as a promising solution to foster the expansion of Grid computing from local area networks to wide area networks.However,by theoretical analysis and simulative evaluation of Grid job blocking in the distributed call and connection setup process of ASON,this paper verifies that ASON and the conventional admission control mechanism confront a problem in supporting future large-scale Grid computing.In order to address this issue,a novel dynamic call and connection admission control(DCCAC)scheme is proposed to improve the network performance and guarantee quality of service(QoS)of Grid applications.This scheme is applicable with complete network information,no network information and partial network information.Numerical results show that the DCCAC scheme can improve the efficiency of the network to a great extent.Moreover,all the analysis and algorithms in this paper are based on ITU-T ASON recommendations,which make the DCCAC scheme more applicable in network engineering for future Grid computing.     

Building a bridge between performance management,radical innovation,and innovation networks: A systematic literature review

Research on performance management (PM) of networks and radical innovation has largely developed along two isolated paths. On the one hand, a growing body of knowledge addresses the use of performance management systems in the context of networks (notably for production and incremental innovation). On the other hand, radical innovation scholars have shown how innovation initiatives that are more uncertain demand the use of new approaches (e.g., new project management routines or different evaluative tools for portfolios). Some scholars even suggest that traditional PM may suppress radical innovation. Our study takes a different approach. It aims to bridge radical innovation and network performance management through a systematic review of the literature. Here, we adopt a hybrid approach that combines bibliometrics with content analysis. Whereas the literature often separates the issues of network performance management and radical innovation, our contribution expands the theory of network management and radical innovation by developing a conceptual framework based on these concepts, thus combining them. We also offer suggestions for further research on this approach. Our framework suggests that overall, the performance management of radical innovation networks presents different features (e.g., recursive rather than linear) and constructs (e.g., openness and unintended performance) from those of innovation network management.     

光网络流量工程的控制机制研究

密集波分复用DWDM(DenseWavelengthDivisionMultiplex)光网络有着十分丰富的带宽,并且能够根据实时需要提供带宽,所以逐渐成为Internet骨干核心网。该文提出一种在光网络中实施流量工程TE(TrafficEngineering)的建议,尤其突出了多协议波长交换MPLS(Multi-ProtocolLambdaSwitch)控制平面和DWDM网络的综合。首先简单描述了光交叉连接OXC(OpticalCrossConnect)的一些基本概念,并介绍了利用TE管理器在两个或多个域之间进行组合控制的概念。进一步定义了在网络单元(如OXC,标记交换路由器LSR(LabelSwitchRouter),TE管理器)之间进行交互的控制消息。并介绍了TE管理的流程,包括动态带宽预留,快速恢复和回收网络资源。     

Agent-based approach to analyzing the effects of dynamic ridesharing in a multimodal network

An agent-based modeling for dynamic ridesharing in a multimodal network is proposed in this paper. The study aims to evaluate the performance of dynamic ridesharing system within a multimodal network and explore the competing mechanism between dynamic ridesharing and public transit, with the presence of managed lane facility. The modeling process simulates the interaction between travelers and the network, and applies a heuristic algorithm to model travelers' decision making process under uncertainty. The model is applicable to networks with varying demographics. Multiple scenarios based on the classic Sioux Falls network have been examined. The modeling results demonstrate that the effects of dynamic ridesharing on a network differ with traffic demand and market penetrations of various travel modes. In networks with high travel demand and low market penetration of public transit, the benefits of dynamic ridesharing system on reducing congestion and providing reliable travel time are quite limited. To enhance the effectiveness of dynamic ridesharing, traffic operators may consider project investments on managed lane facilities. In networks with high market penetration of public transit, dynamic ridesharing may attract large amounts of short distance trips and aggravate congestion, especially at the initial launching phase. Policy makers would want to ensure that the existing infrastructure is sufficient to accommodate the extra traffic induced by ridesharing. Ridesharing service providers might also consider proper strategies to avoid “abuse” of the system by short trips and accelerate the market penetration.     

The q-Ad Hoc Hub Location Problem for Multi-modal Networks

This research proposes a spatial optimization problem over a multi-modal transportation network, termed the q-Ad-hoc hub location problem (AHLP), to utilize alternative hubs in an ad-hoc manner in the wake of a hub outage. The model aims to reorganize the spatial structure of disrupted networks: unaffected hubs are utilized as ad-hoc hubs through which alternative routes connect supply and demand nodes. As a case study, the AHLP is applied to a multi-modal freight transport system connecting international destinations with the United States. The models are utilized to establish a new ranking methodology for critical infrastructure by combining metrics capturing nodal criticality and network resilience and recuperability. The results show that the AHLP is both an effective and practical recovery approach for a hub network to respond to the potential disruptions of hubs and a novel methodology for ranking critical infrastructure.     

Pruned Feed-forward Networks for Efficient Implementation of Multiple FIR Filters with Arbitrary Frequency Responses

A new algorithm is presented for efficient implementation of multiple FIR filters in real-time applications. We introduce an analogy between the multiple FIR filters and linear feed-forward networks, and show how the FIR filters with any frequency characteristics may be designed by a learning algorithm of the network with proper choice of training patterns. Starting from a fully-connected feed-forward architecture, more efficient network architectures may be obtainable by pruning connection weights with minor contributions. For demonstration we design feed-forward networks for 16 bandpass cochlear filters with much less connection weights and moderate performance degradation.     

MANET路由协议及其性能研究

MANET(Mobile Ad Hoe Network)是由一组无线移动主机组成的一个没有任何建立好的基础设施或集中管理设备的临时网络。网络拓扑易变、带宽、能源有限是Ad Hoc移动网络的主要特点。重点介绍了Ad hoc网络的组网关键技术——路由协议，并对现在的具有代表性的协议性能进行了比较，研究了在不同环境下的各自路由协议仿真实验所体现出来的性能差别，对Ad hoc的组网具有指导意义。     

Superimposing neural learning by dynamic and spatial changing weights

In this article, a new neural network model is presented for incremental learning tasks where networks are required to learn new knowledge without forgetting the old. An essential core of the proposed network structure is their dynamic and spatial changing connection weights (DSCWs). A learning scheme is developed for the formulation of the dynamic changing weights, while a structural adaptation is formulated by the spatial changing connecting weights. To avoid disturbing the old knowledge by the creation of new connections, a restoration mechanism is introduced dusing the DSCWs. The usefulness of the proposed model is demonstrated by using a system identification task. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002.     

基于动态连接的RDMA可靠传输协议设计

未来100P/E级高性能计算机系统对网络的传输可靠性、性能均衡性、可扩展性方面有更高的需求。本文提出的RDMA传输模型,采取配置少量资源,动态连接使用的策略实现端到端的数据可靠传输。与传统的可靠通信协议如Infiniband相比,本方案的优势为:(1)支持自动重路由,可绕过网络故障区域保证消息的可靠传输;(2)支持报文乱序到达,支持源和目的间的多路径传输,提供消息的流控机制,能较好地均衡网络整体性能,减少网络热点和缓解网络拥塞;(3)基于通信接口硬件实现可靠性数据结构,不需要消耗主存为通信建立连接,具有极高的系统可扩展性。初步测试结果表明,采取了优化措施后,该协议不会增加小于4K字节消息的传输延迟。     

Dynamic impacts of commodity flow disruptions in inland waterway networks

Freight and passenger transport in the US is projected to increase substantially by 2035 making a strong case for greater usage of the inland waterway barge transport. Inland waterway networks constitute an important component of the US multi-modal transport infrastructure spanning 25,000 miles of navigable routes across 38 states. Risk-based preparedness planning for inland waterway networks requires a means to assess the interdependent impacts associated with closures to inland waterway infrastructure. This study proposes a dynamic framework to assess multi-regional, multi-industry losses due to disruptions on the waterway networks, including ports and waterway links. We investigate simulation-driven disruptive scenarios, such as dock closures, that affect daily commerce across the waterway network and integrate with a dynamic interdependency model to quantify the effect of disruptions on industry inoperability across multiple regions and multiple industries. We implement our framework with a data-driven case study of the operations at the Port of Catoosa on the McClellan–Kerr Arkansas River branch of the Mississippi River Navigation System. Resulting dock-specific, industry-specific, and region-specific insights can guide preparedness decision making.     

Incremental K-clique clustering in dynamic social networks

Clustering entities into dense parts is an important issue in social network analysis. Real social networks usually evolve over time and it remains a problem to efficiently cluster dynamic social networks. In this paper, a dynamic social network is modeled as an initial graph with an infinite change stream, called change stream model, which naturally eliminates the parameter setting problem of snapshot graph model. Based on the change stream model, the incremental version of a well known k-clique clustering problem is studied and incremental k-clique clustering algorithms are proposed based on local DFS (depth first search) forest updating technique. It is theoretically proved that the proposed algorithms outperform corresponding static ones and incremental spectral clustering algorithm in terms of time complexity. The practical performances of our algorithms are extensively evaluated and compared with the baseline algorithms on ENRON and DBLP datasets. Experimental results show that incremental k-clique clustering algorithms are much more efficient than corresponding static ones, and have no accumulating errors that incremental spectral clustering algorithm has and can capture the evolving details of the clusters that snapshot graph model based algorithms miss.     

Development of computer-supported collaborative social networks in a distributed learning community

This study examines the formation and change of collaborative learning social networks in a distributed learning community. A social network perspective is employed to understand how collaborative networks evolved over time when 31 distributed learners collaborated on a design project using a computer-mediated communication system during two semesters. Special attention was paid to how pre-existing friendship networks influenced the formation of macro-level collaborative learning networks and individual level social capital. We discovered that pre-existing friendship networks significantly influenced the formation of collaborative learning networks, but the effect was dependent on the developmental phase of community. Also, pre-existing networks generally acted as a social liability that constrained learners' ability to enhance their social networks and build social capital when they participated in a new learning environment. The results suggest that, in order to fully understand how to build effective collaborative learning and work environments, participants' social network structures need to be considered.     

电力系统通信网技术改造

本文就我国电力数字化建设特别针对京津唐电力通信网的构建进行了全面的分析。详细描述了传统电力系统业务行政电话交换系统从传统通信网向新型数字网络迁移的原因、目的、技术选择及技术实施的全过程。京津唐电力系统选择ATM技术构建通信网络，提供良好网络管理能力，保证各种业务流量的动态分配、流量控制、QoS，支持多种不同带宽的业务和不同网络的联网能力，根据不同业务类型速率的动态调整传榆通道的有效资源，最大的发挥ATM网络宽带传榆能力和使用其多优先级系统为自身以实时性为依托的业务服务c     

A scalable and self-adapting notification framework for healthcare information systems

There has been a great interest in publish/subscribe systems in recent years. This interest, coupled with the pervasiveness of light-weight electronic devices, such as cellular phones and personal digital assistants, has opened a new arena in publish/subscribe networks. Currently, many broker overlay networks are static and rarely change in structure. Often, a network overlay structure is predefined or manually modified. This paper presents a dynamic broker network for disseminating critical lab and patient information in a Healthcare information system. The reported work builds upon previous network optimization research on ad hoc publish/subscribe networks. The underlying framework utilizes user-defined cost functions to satisfy quality of service constraints. In essence, the broker network optimization problem is reduced to an incremental search problem to generate low cost network configurations. Certain reliability issues are also addressed by providing a scheduling algorithm to selectively retransmit information and handle broker connectivity failures.