Continuum Traffic Simulation

We present a novel method for the synthesis and animation of realistic traffic flows on large‐scale road networks. Our technique is based on a continuum model of traffic flow we extend to correctly handle lane changes and merges, as well as traffic behaviors due to changes in speed limit. We demonstrate how our method can be applied to the animation of many vehicles in a large‐scale traffic network at interactive rates and show that our method can simulate believable traffic flows on publicly‐available, real‐world road data. We furthermore demonstrate the scalability of this technique on many‐core systems.     

State‐of‐the‐Art in GPU‐Based Large‐Scale Volume Visualization

This survey gives an overview of the current state of the art in GPU techniques for interactive large‐scale volume visualization. Modern techniques in this field have brought about a sea change in how interactive visualization and analysis of giga‐, tera‐ and petabytes of volume data can be enabled on GPUs. In addition to combining the parallel processing power of GPUs with out‐of‐core methods and data streaming, a major enabler for interactivity is making both the computational and the visualization effort proportional to the amount and resolution of data that is actually visible on screen, i.e. ‘output‐sensitive’ algorithms and system designs. This leads to recent output‐sensitive approaches that are ‘ray‐guided’, ‘visualization‐driven’ or ‘display‐aware’. In this survey, we focus on these characteristics and propose a new categorization of GPU‐based large‐scale volume visualization techniques based on the notions of actual output‐resolution visibility and the current working set of volume bricks—the current subset of data that is minimally required to produce an output image of the desired display resolution. Furthermore, we discuss the differences and similarities of different rendering and data traversal strategies in volume rendering by putting them into a common context—the notion of address translation. For our purposes here, we view parallel (distributed) visualization using clusters as an orthogonal set of techniques that we do not discuss in detail but that can be used in conjunction with what we present in this survey.     

Visual Exploration of Dynamic Multichannel EEG Coherence Networks

Electroencephalography (EEG) coherence networks represent functional brain connectivity, and are constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Visualization of such networks can provide insight into unexpected patterns of cognitive processing and help neuroscientists to understand brain mechanisms. However, visualizing dynamic EEG coherence networks is a challenge for the analysis of brain connectivity, especially when the spatial structure of the network needs to be taken into account. In this paper, we present a design and implementation of a visualization framework for such dynamic networks. First, requirements for supporting typical tasks in the context of dynamic functional connectivity network analysis were collected from neuroscience researchers. In our design, we consider groups of network nodes and their corresponding spatial location for visualizing the evolution of the dynamic coherence network. We introduce an augmented timeline‐based representation to provide an overview of the evolution of functional units (FUs) and their spatial location over time. This representation can help the viewer to identify relations between functional connectivity and brain regions, as well as to identify persistent or transient functional connectivity patterns across the whole time window. In addition, we introduce the time‐annotated FU map representation to facilitate comparison of the behaviour of nodes between consecutive FU maps. A colour coding is designed that helps to distinguish distinct dynamic FUs. Our implementation also supports interactive exploration. The usefulness of our visualization design was evaluated by an informal user study. The feedback we received shows that our design supports exploratory analysis tasks well. The method can serve as a first step before a complete analysis of dynamic EEG coherence networks.     

Route‐Aware Edge Bundling for Visualizing Origin‐Destination Trails in Urban Traffic

Origin‐destination (OD) trails describe movements across space. Typical visualizations thereof use either straight lines or plot the actual trajectories. To reduce clutter inherent to visualizing large OD datasets, bundling methods can be used. Yet, bundling OD trails in urban traffic data remains challenging. Two specific reasons hereof are the constraints implied by the underlying road network and the difficulty of finding good bundling settings. To cope with these issues, we propose a new approach called Route Aware Edge Bundling (RAEB). To handle road constraints, we first generate a hierarchical model of the road‐and‐trajectory data. Next, we derive optimal bundling parameters, including kernel size and number of iterations, for a user‐selected level of detail of this model, thereby allowing users to explicitly trade off simplification vs accuracy. We demonstrate the added value of RAEB compared to state‐of‐the‐art trail bundling methods on both synthetic and real‐world traffic data for tasks that include the preservation of road network topology and the support of multiscale exploration.     

A robust adaptive congestion control strategy for large scale networks with differentiated services traffic

In this paper, a robust decentralized congestion control strategy is developed for a large scale network with Differentiated Services (Diff-Serv) traffic. The network is modeled by a nonlinear fluid flow model corresponding to two classes of traffic, namely the premium traffic and the ordinary traffic. The proposed congestion controller does take into account the associated physical network resource limitations and is shown to be robust to the unknown and time-varying delays. Our proposed decentralized congestion control strategy is developed on the basis of Diff-Serv architecture by utilizing a robust adaptive technique. A Linear Matrix Inequality (LMI) condition is obtained to guarantee the ultimate boundedness of the closed-loop system. Numerical simulation implementations are presented by utilizing the QualNet and Matlab software tools to illustrate the effectiveness and capabilities of our proposed decentralized congestion control strategy.     

Visual Analysis of Governing Topological Structures in Excitable Network Dynamics

To understand how topology shapes the dynamics in excitable networks is one of the fundamental problems in network science when applied to computational systems biology and neuroscience. Recent advances in the field discovered the influential role of two macroscopic topological structures, namely hubs and modules. We propose a visual analytics approach that allows for a systematic exploration of the role of those macroscopic topological structures on the dynamics in excitable networks. Dynamical patterns are discovered using the dynamical features of excitation ratio and co‐activation. Our approach is based on the interactive analysis of the correlation of topological and dynamical features using coordinated views. We designed suitable visual encodings for both the topological and the dynamical features. A degree map and an adjacency matrix visualization allow for the interaction with hubs and modules, respectively. A barycentric‐coordinates layout and a multi‐dimensional scaling approach allow for the analysis of excitation ratio and co‐activation, respectively. We demonstrate how the interplay of the visual encodings allows us to quickly reconstruct recent findings in the field within an interactive analysis and even discovered new patterns. We apply our approach to network models of commonly investigated topologies as well as to the structural networks representing the connectomes of different species. We evaluate our approach with domain experts in terms of its intuitiveness, expressiveness, and usefulness.     

Repairing Inconsistent Curve Networks on Non‐parallel Cross‐sections

In this work we present the first algorithm for restoring consistency between curve networks on non‐parallel cross‐sections. Our method addresses a critical but overlooked challenge in the reconstruction process from cross‐sections that stems from the fact that cross‐sectional slices are often generated independently of one another, such as in interactive volume segmentation. As a result, the curve networks on two non‐parallel slices may disagree where the slices intersect, which makes these cross‐sections an invalid input for surfacing. We propose a method that takes as input an arbitrary number of non‐parallel slices, each partitioned into two or more labels by a curve network, and outputs a modified set of curve networks on these slices that are guaranteed to be consistent. We formulate the task of restoring consistency while preserving the shape of input curves as a constrained optimization problem, and we propose an effective solution framework. We demonstrate our method on a data‐set of complex multi‐labeled input cross‐sections. Our technique efficiently produces consistent curve networks even in the presence of large errors.     

对等网络的拥塞研究

对等网络的普遍应用带来了网络拥塞。从对等网络的拓扑属性研究网络拥塞，首先分析真实的Gnutella网络的流量，确定节点介数与网络拥塞之间存在关系。接着根据排队论模型从理论上给出了导致网络拥塞的临界负载与网络拓扑属性介数的公式解。最后设计拥塞控制策略，通过增加具有大介数节点的容量和这些节点间连接的方法来减轻网络拥塞。     

Markovian jump guaranteed cost congestion control strategies for large scale mobile networks with differentiated services traffic

In this paper, two novel congestion control strategies for mobile networks with differentiated services (Diff-Serv) traffic are presented, namely (i) a Markovian jump decentralized guaranteed cost congestion control strategy, and (ii) a Markovian jump distributed guaranteed cost congestion control strategy. The switchings or changes in the network topology are modeled by a Markovian jump process. By utilizing guaranteed cost control principles, the proposed congestion control schemes do indeed take into account the associated physical network resource constraints and are shown to be robust to unknown and time-varying network latencies and time delays. A set of Linear Matrix Inequality (LMI) conditions are obtained to guarantee the QoS of the Diff-Serv traffic with a guaranteed upper bound cost. Simulation results are presented to illustrate the effectiveness and capabilities of our proposed strategies. Comparisons with centralized and other relevant works in the literature focused on Diff-Serv traffic and mobile networks are also provided to demonstrate the advantages of our proposed solutions.     

An Interactive Visualization System for Large Sets of Phase Space Trajectories

We introduce a visual analysis system with GPU acceleration techniques for large sets of trajectories from complex dynamical systems. The approach is based on an interactive Boolean combination of subsets into a Focus+Context phase‐space visualization. We achieve high performance through efficient bitwise algorithms utilizing runtime generated GPU shaders and kernels. This enables a higher level of interactivity for visualizing the large multivariate trajectory data. We explain how our design meets a set of carefully considered analysis requirements, provide performance results, and demonstrate utility through case studies with many‐particle simulation data from two application areas.     

基于复杂网络的路网交通拥堵评估仿真模型

为了能够深入分析路网交通拥堵动态演进过程, 为交通拥堵治理提供决策分析工具, 提出了一个基于复杂网络的路网拥堵评估仿真模型。通过将路段阻抗概念引入复杂网络理论, 实现了路网拓扑模型和流量模型的结合; 此外, 还提出了虚拟测试车辆遍历的路网通行能力评估方法, 对不同路网条件下的道路通行能力进行评估。最后在PC系统上实现了完整的路网拥堵评估仿真系统, 并利用该系统对拥堵路段数量、交通流量和路网拓扑结构等因素对路网通行能力的影响进行了仿真分析。仿真实验结果与经典交通理论分析结果一致, 并能反映更多的动态过程信息, 表明该模型能够准确有效地进行交通路网拥堵评估, 可以为相应的交通拥堵管理决策提供依据。     

Visual Analysis of protein‐ligand interactions

The analysis of protein‐ligand interactions is complex because of the many factors at play. Most current methods for visual analysis provide this information in the form of simple 2D plots, which, besides being quite space hungry, often encode a low number of different properties. In this paper we present a system for compact 2D visualization of molecular simulations. It purposely omits most spatial information and presents physical information associated to single molecular components and their pairwise interactions through a set of 2D InfoVis tools with coordinated views, suitable interaction, and focus+context techniques to analyze large amounts of data. The system provides a wide range of motifs for elements such as protein secondary structures or hydrogen bond networks, and a set of tools for their interactive inspection, both for a single simulation and for comparing two different simulations. As a result, the analysis of protein‐ligand interactions of Molecular Simulation trajectories is greatly facilitated.     

Visualizing large telecommunication data sets

Global telecommunication services create an enormous volume of real time data. Long distance voice networks, for example, can complete more than 250 million calls a day; wide area data networks can support many hundreds of thousands of virtual circuits and millions of Internet protocol (IP) flows and Web server sessions. Unlike terabyte databases, which typically contain images or multimedia streams, telecommunication databases mainly contain numerous small records describing transactions and network status events. The data processing involved therefore differs markedly, both in the number of records and the data items interpreted. To efficiently configure and operate these networks, as well as manage performance and reliability for the user, these vast data sets must be understandable. Increasingly, visualization proves key to achieving this goal. AT&T Infolab is an interdisciplinary project created in 1996 to explore how software, data management and analysis, and visualization can combine to attack information problems involving large scale networks. The data Infolab collects daily reaches tens of gigabytes. The Infolab project Swift-3D uses interactive 3D maps with statistical widgets, topology diagrams, and pixel oriented displays to abstract network data and let users interact with it. We have implemented a full scale Swift-3D prototype, which generated the examples presented     

Social Network Clustering and Visualization using Hierarchical Edge Bundles

The hierarchical edge bundle (HEB) method generates useful visualizations of dense graphs, such as social networks, but requires a predefined clustering hierarchy, and does not easily benefit from existing straight‐line visualization improvements. This paper proposes a new clustering approach that extracts the community structure of a network and organizes it into a hierarchy that is flatter than existing community‐based clustering approaches and maps better to HEB visualization. Our method not only discovers communities and generates clusters with better modularization qualities, but also creates a balanced hierarchy that allows HEB visualization of unstructured social networks without predefined hierarchies. Results on several data sets demonstrate that this approach clarifies real‐world communication, collaboration and competition network structure and reveals information missed in previous visualizations. We further implemented our techniques into a social network visualization application on facebook.com and let users explore the visualization and community clustering of their own social networks.     

Example‐Based Fractured Appearance

A common weathering effect is the appearance of cracks due to material fractures. Previous exemplar‐based aging and weathering methods have either reused images or sought to replicate observed patterns exactly. We introduce a new approach to exemplar‐based modeling that creates weathered patterns on synthetic objects by matching the statistics of fracture patterns in a photograph. We present a user study to determine which statistics are correlated to visual similarity and how they are perceived by the user. We then describe a revised physically‐based fracture model capable of producing a wide range of crack patterns at interactive rates. We demonstrate how a Bayesian optimization method can determine the parameters of this model so it can produce a pattern with the same key statistics as an exemplar. Finally, we present results using our approach and various exemplars to produce a variety of fracture effects in synthetic renderings of complex environments. The speed of the fracture simulation allows interactive previews of the fractured results and its application on large scale environments.     

Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization

Analyzing molecular dynamics (MD) simulations is a key aspect to understand protein dynamics and function. With increasing computational power, it is now possible to generate very long and complex simulations, which are cumbersome to explore using traditional 3D animations of protein movements. Guided by requirements derived from multiple focus groups with protein engineering experts, we designed and developed a novel interactive visual analysis approach for long and crowded MD simulations. In this approach, we link a dynamic 3D focus+context visualization with a 2D chart of time series data to guide the detection and navigation towards important spatio‐temporal events. The 3D visualization renders elements of interest in more detail and increases the temporal resolution dependent on the time series data or the spatial region of interest. In case studies with different MD simulation data sets and research questions, we found that the proposed visual analysis approach facilitates exploratory analysis to generate, confirm, or reject hypotheses about causalities. Finally, we derived design guidelines for interactive visual analysis of complex MD simulation data.     

Interactive 3D visualization for wireless sensor networks

Wireless sensor networks open up a new realm of ubiquitous computing applications based on distributed large-scale data collection by embedded sensor nodes that are wirelessly connected and seamlessly integrated within the environment. 3D visualization of sensory data is a challenging issue, however, due to the large number of sensors used in typical deployments, continuous data streams, and constantly varying network topology. This paper describes a practical approach for interactive 3D visualization of wireless sensor network data. A regular 3D grid is reconstructed using scattered sensor data points and used to generate view-dependent 2D slices that are consequently rendered with commodity graphics hardware leading to smooth visualization over space and time. Furthermore, the use of efficient space partitioning data structures and the independent processing of sensor data points facilitates interactive rendering for large number of sensors while accommodating constantly changing network topology. The practical value of the proposed method is demonstrated and results obtained for visualizing time-varying temperature distributions in an urban area are presented.     

一种改进的基于Smith原则的计算机高速通信网络的拥塞控制方案

1.引言 ATM网络是一类虚拟的电路交换网络,它融入了电路交换技术和包交换技术。在这两个系统融入以前它们是独立的,若要互相通信必须获得彼此的通信参数才能建立虚拟连接。而ATM网络通过存储技术和统计复用来共享网络资源,网络资源的共享使得通信费用大大减少。ATM是以定长的信元(cell)作为高速通信信息的载体,它具有高速、低比特错误率、动态分配带宽和高复合能力的优点,这些使得它非常适宜于需要保证服务质量(Quality of Service,QoS)的多媒体数据流。由于多媒体业务流的特性,常引起网络拥塞并降低服务的质量。因此必须采取一定的流量管理控制机制来避免网络的拥塞。     

Restoration by path concatenation: fast recovery of MPLS paths

A new general theory about restoration of network paths is first introduced. The theory pertains to restoration of shortest paths in a network following failure, e.g., we prove that a shortest path in a network after removing k edges is the concatenation of at most k+1 shortest paths in the original network. The theory is then combined with efficient path concatenation techniques in MPLS (multi-protocol label switching), to achieve powerful schemes for restoration in MPLS based networks. We thus transform MPLS into a flexible and robust method for forwarding packets in a network. Finally, the different schemes suggested are evaluated experimentally on three large networks (a large ISP, the AS graph of the Internet, and the full Internet topology). These experiments demonstrate that the restoration schemes perform well in actual topologies. Received: December 2001 / Accepted: July 2002 RID="*" ID="*" This research was supported by a grant from the Ministry of Science, Israel     

Evalvid-RA: trace driven simulation of rate adaptive MPEG-4 VBR video

Due to the increasing deployment of conversational real-time applications like VoIP and videoconferencing, the Internet is today facing new challenges. Low end-to-end delay is a vital QoS requirement for these applications, and the best effort Internet architecture does not support this natively. The delay and packet loss statistics are directly coupled to the aggregated traffic characteristics when link utilization is close to saturation. In order to investigate the behavior and quality of such applications under heavy network load, it is therefore necessary to create genuine traffic patterns. Trace files of real compressed video and audio are text files containing the number of bytes per video and audio frame. These can serve as material to construct mathematical traffic models. They can also serve as traffic generators in network simulators since they determine the packet sizes and their time schedule. However, to inspect perceived quality, the compressed binary content is needed to ensure decoding of received media. The EvalVid streaming video tool-set enables this using a sophisticated reassembly engine. Nevertheless, there has been a lack of research solutions for rate adaptive media content. The Internet community fears a congestion collapse if the usage of non-adaptive media content continues to grow. This paper presents a solution named Evalvid-RA for the simulation of true rate adaptive video. The solution generates real rate adaptive MPEG-4 streaming traffic, using the quantizer scale for adjusting the sending rate. A feedback based VBR rate controller is used at simulation time, supporting TFRC and a proprietary congestion control system named P-AQM. Example ns-2 simulations of TFRC and P-AQM demonstrate Evalvid-RA’s capabilities in performing close-to-true rate adaptive codec operation with low complexity to enable the simulation of large networks with many adaptive media sources on a single computer.