基于小波分析的交通数据自适应消噪算法研究

针对实际采样环境中存在的各种干扰,以及交通数据的非平稳特性,在交通数据小波变换特性分析的基础上,提出基于小波分析的交通数据自适应消噪算法:对交通数据进行小波分解,然后对高频系数的自相关函数进行白噪声检验,从而确定小波分解的层数和阈值。采用实际检测交通流数据,对算法的有效性进行了验证分析。     

Edge Pricing of Multicommodity Networks for Selfish Users with Elastic Demands

We examine how to induce selfish heterogeneous users in a multicommodity network to reach an equilibrium that minimizes the social cost. In the absence of centralized coordination, we use the classical method of imposing appropriate taxes (tolls) on the edges of the network. We significantly generalize previous work (Yang and Huang in Transp. Res. Part B 38:1–15, [2004]; Karakostas and Kolliopoulos in Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science, pp. 268–276, [2004]; Fleischer et al. in Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science, pp. 277–285, [2004]) by allowing user demands to be elastic. In this setting the demand of a user is not fixed a priori but it is a function of the routing cost experienced, a most natural assumption in traffic and data networks. Research supported by MITACS and a NSERC Discovery grant.     

Direction coding using a tactile chair

This laboratory study examined the possibility of using a car seat instrumented with a tactile display to communicate directional information to a driver. A car seat fitted with an 8 × 8 matrix of vibrators embedded in the seat pan was used to code eight different directions. Localization response time and angular accuracy were examined as a function of stimulus direction, presence of a tactile attention cue, temporal pattern, stimulus layout, age, and gender. The mean absolute angular error was 23°, and both localization accuracy and response times were superior for the back left, backward, and back right directions. Of the various temporal pattern/attention cue combinations examined, results favored the relatively fast patterns consisting of vibration bursts of 125 or 250 ms without a centrally located attention cue over 500 ms bursts that were preceded by an attention cue. Observed age and gender effects were relatively modest, suggesting that using tactile cueing to communicate direction is effective across a wide range of users. In addition, the tactile stimulus was detected by more than 90% of the participants under surprise trial conditions. Overall, these results indicate that the tactile chair provides a promising and robust method of providing directional information.     

A novel self-organizing fuzzy rule-based system for modelling traffic flow behaviour

The study and development of transportation systems have been a focus of attention in recent years, with many research efforts directed in particular at modelling traffic behaviour from both macroscopic and microscopic points of views. Although many statistical regression models of road traffic relationships have been formulated, they have proven to be unsuitable due to multiple and ill-defined traffic characteristics. Alternative methods such as neural networks have thus been sought but, despite some promising results, their design remains problematic and implementation is equally difficult. Another salient issue is that the opaqueness of trained networks prevents understanding the underlying models. Hybrid neuro-fuzzy rule-based systems, which combine the complementary capabilities of both neural networks and fuzzy logic, constitute a more promising technique for modelling traffic flow. This paper describes the application of a specific class of neuro-fuzzy system known as the Pseudo Outer-Product Fuzzy-Neural Network using Truth-Value-Restriction method (POPFNN-TVR) for modelling traffic behaviour. This approach has been shown to perform better on such problems than similar architectures. The results obtained highlight the capability of POPFNN-TVR in fuzzy knowledge extraction for modelling inter-lane relationships in a highway traffic stream, as well as in generalizing from sample data, as compared to traditional feed-forward neural networks using back-propagation learning. The model thus obtained automatically can be understood, analysed, and readily applied for transportation planning.     

Stability of Local On‐Ramp Metering Control Laws

A framework for stability analysis of local on‐ramp metering control strategies based on the cell transmission model is presented. Within this framework, it is possible to formulate Lyapunov and input‐state stability results for on‐ramp metering control strategies in an open section of highway with on‐ramps. Using this analysis, recommendations for the design of on‐ramp metering control laws set points are derived. Two examples on the use of such analysis are presented. One deals with the stability analysis of a local on‐ramp metering control law and the other with the design of a disturbance observer that, used in combination with the local on‐ramp metering control law, provides a more robust response to traffic regulation. Simulation results are included that confirm the possibility of using this framework to test the impact of local on‐ramp metering control strategies.     

一种新型的BoD带宽请求分配算法

BoD协议中 可以 通过充分利用按需分配后剩余的带宽来降低时延。首先针对如何高效地利用剩余带宽及其对反馈控制的影响,提出了一种新型的基于预测和星上反馈控制的BoD带宽请求分配算法。其次根据网络流量同时呈现长相关和短相关特性,提出采用ARFIMA(p,d,q)模型进行流量建模与预测,该模型根据参数d的取值不同既能表示长相关又能表示短相关。最后利用OPNET软件建立仿真系统。仿真结果表明,对于长相关和短相关业务流,基于ARFIMA(p,d,q)模型预测和星上反馈控制的BoD带宽请求分配方案能够最高效地利用剩余带宽来降低时延。     

基于动态流量的多拓扑链路权值优化算法

针对网络流量动态变化和不同流量对拥塞控制和传输代价的要求不同的现象,提出一种基于小生境粒子群的多拓扑路由子层链路权值优化算法。该算法以适应网络流量动态变化为目标,设置了以时段划分的业务量矩阵和适应流量动态变化要求的权重因子。优化目标函数从拥塞代价影响和传输代价影响两方面进行了改进,并利用小生境粒子群算法对目标函数进行寻优,以解决一般优化算法存在的容易陷入局部最优的问题。实验结果表明,算法能够在网络中实现负载均衡。     

Analytical derivation of traffic patterns in cache-coherent shared-memory systems

This paper presents an analytical method to derive the worst-case traffic pattern caused by a task graph mapped to a cache-coherent shared-memory system. Our analysis allows designers to rapidly evaluate the impact of different mappings of tasks to IP cores on the traffic pattern. The accuracy varies with the application’s data sharing pattern, and is around 65% in the average case and 1% in the best case when considering the traffic pattern as a whole. For individual connections, our method produces tight worst-case bandwidths.     

QoS-based cooperative algorithm for integral multi-commodity flow problem

This paper treats with integral multi-commodity flow through a network. To enhance the Quality of Service (QoS) for channels, it is necessary to minimize delay and congestion. Decreasing the end-to-end delay and consumption of bandwidth across channels are dependent and may be considered in very complex mathematical equations. To capture with this problem, a multi-commodity flow model is introduced whose targets are minimizing delay and congestion in one model. The flow through the network such as packets, also needs to get integral values. A model covering these concepts, is NP-hard while it is very important to find transmission strategies in real-time. For this aim, we extend a cooperative algorithm including traditional mathematical programming such as path enumeration and a meta-heuristic algorithm such as genetic algorithm. To find integral solution satisfying demands of nodes, we generalize a hybrid genetic algorithm to assign the integral commodities where they are needed. In this hybrid algorithm, we use feasible encoding and try to keep feasibility of chromosomes over iterations. By considering some random networks, we show that the proposed algorithm yields reasonable results in a few number of iterations. Also, because this algorithm can be applied in a wide range of objective functions in terms of delay and congestion, it is possible to find some routs for each commodity with high QoS. Due to these outcomes, the presented model and algorithm can be utilized in a variety of application in computer networks and transportation systems to decrease the congestion and increase the usage of channels.     

A study of traffic, user behavior and pricing policies in a large campus network

Tsinghua University campus network is a large campus network in China, providing volume-based and flat-rate Internet access service for more than 31,000 students and staff. In order to better understand its traffic, user behavior and pricing policies to facilitate network planning and management, we collect a one-year-long flow-based traffic log and a 10-year-long user-based log at the boundary of this campus network, and then conduct an analysis study on these two data sets. In this paper, we first present characteristics of inbound traffic flows from the aspects of traffic prediction and inference. Then we analyze the geographical origins of incoming flows, and the result reveals that USA, Japan and Korea are the most important source countries of international traffic. Our user-based investigation shows that the properties of users have important influence on their behavior, e.g., major has stronger influence on users’ online time, while occupation has stronger influence on users’ international traffic volume. We also find that there are more and more users choosing flat rate pricing scheme instead of volume based pricing scheme, and these users tend to over-provision when they subscribe from tiered pricing options.