基于模糊故障树的地铁综合监控系统可靠性分析

近年城市交通问题凸显,地铁作为解决城市交通问题的重要方式,其安全稳定运行显得尤为重要。地铁综合监控系统是整个地铁系统安全可靠运行的重要保障,对其可靠性进行有效的评估有着重要的价值。介绍了地铁综合监控系统和模糊故障树理论,运用模糊故障树对地铁综合监控系统可靠性进行分析,并对车站级监控系统的故障进行了定性和定量的可靠性分析,拓展了模糊故障树的使用领域。     

iCentroView:城市交通监控与管理系统

随着经济的高速发展,城市交通问题也越来越突出,交通拥堵程度和交通事故率不断上升,建立先进的智能交通系统可以很好地缓解这一问题。本文介绍了一种城市交通监控与管理系统,以地理信息系统为基础,构建交通控制与交通信息数据管理为一体的城市交通监控指挥平台,根据静态和实时的交通数据分析预测道路交通状况,为交通管理部门提供技术支持,充分有效利用交通资源。     

城市交通视频监控新动向

全国各地经过10年左右的城市交通视频监控系统的建设，已经为改善城市交通环境带来了明显的效益。但是随着私家车的快速发展，又再凸显出城市交通道路建设的严重滞后。随着网络视频系统不断扩大的需求，现有的解决方案已逐渐不敷使用，本文将探讨未来交通视频监控网络化、智能化、移动化以及商业化的新动向。     

城市道路监控系统解决方案

城市道路监控因其实时及直观性对交通部门指挥城市交通起到了一定作用，本文提出了以网络视频服务器为核心的城市道路监控解决方案．值得一读。     

基于IPv6智能交通指挥系统

利用最新网络技术IPv6来实现路网视频信息的上传,经过智能交通监控指挥中心的数据处理,采用计算机视觉识别技术,自动提取城市路网的交通信息及参数．再通过IPv6下一代互联网的网络传榆方法进行城市交通诱导指挥以及路网交通的智能监控。本文讨论智能交通监控指挥系统的总体结构、城市路网交通参数的自动提取子系统、智能交通监控予系统和城市交通指挥子系统。     

基于城市交通大数据的车辆类别挖掘及应用分析

实时城市交通监控已成为现代城市管理的一个重要组成部分，视频监控采集的交通大数据在城市管理和交通控制方面得到了越来越多的应用；然而，全城范围内庞大的监控交通大数据还鲜少用于城市交通及城市计算研究。在一个省会城市全城范围内的监控交通大数据上展开了车辆类别挖掘及应用分析研究。首先，定义了周期性私家车、类出租车和公共通勤车三种对城市交通具有重要影响的车辆类别，将车辆类别定义与频繁序列模式挖掘算法相结合提出了相应的挖掘方法。在济南市一周1704个视频监测点，1.2亿次车辆记录数据上，验证了所提定义及挖掘方法的有效性；其次，以4个居民小区为例挖掘分析了居民出行的交通方式及与周围兴趣点（POI）分布关系，此外，还探索了城市交通大数据与POI相结合在城市规划、需求预测和偏好推荐方面的应用潜能。     

iCentroView系统中的系统联动设计

本文分析了城市智能交通监控与管理系统（iCentroView）及其与系统联动的关系,介绍了城市交通监控与管理系统体系架构下的系统集成联动,并以部署在浙江省桐乡市交通指挥中心为例说明系统联动的实现。     

基于GPRS的城市交通监控系统研究

GPRS具有无时延、覆盖面广、按流量收费等优点,因此该系统以较低的费用即可实现对全网交通的全面监控,提高了交通监控的实时性。对基于GPRS的城市交通系统进行了分析和设计。     

组态王软件在交通管理中心的应用

介绍了交通监控系统,详细描述了系统底层PLC和顶层组态王软件的设计。使得工作人员只要在交通管理中心,就可以监控到该城市的主要十字路口的交通信号灯的状态,并可以针对不同地段不同时间段车流量优化底层PLC控制,提高城市交通管理效益。     

iCentroView系统中的GIS设计与实现

城市交通监控与管理系统（iCentroView）是根据我国城市交通的基本情况和智能交通的发展现状而设计实现的智能交通系统,地理信息系统（GIS）是iCentroView系统的基础,本文根据iCentroView系统的需求,设计实现了一个GIS,并且在实际运行中对iCentroView系统有很好的支持,效果良好。     

Presenting a traffic management and control system in driver assistance form based on vehicular networks

Vehicular Networks is considered a major step in the field of Intelligent Transportation System (ITS). In this technology, some equipment will be installed on vehicles and special places at roadsides which will enable the wireless communication between vehicles with each other and will provide the communication between the vehicles and roadside equipment. One of the ITS application is Traffic monitoring system. Such system enables accessing traffic videos by traffic monitoring centers to make traffic decision. However, providing traffic video for the vehicles can be appealing. This paper addresses a new application in vehicular networks and ITS which can provide this videos for drivers in a city. Each driver request timely traffic video of a location from a web server and the web server forward this request to a stream management server. This server based on current location of the requester vehicle, its speed and its direction calculates appropriate video chunks for each RSU along vehicle destination. This study aims to present a system which can bring a high accessibility for content and can provide it with an appropriate bandwidth and quality for vehicles. Due to the scalability and bandwidth limitations for its content and streaming, vehicular networks are used in this system.     

主动接纳策略的Web集群多维QoS目标优化调度算法

针对以往的调度算法对服务器本身的研究较多，而结合网络流量特征采取相应调度策略研究较少的情况．提出了一种结合网络自相似访问特征的接纳控制策略，分析了一种综合考虑Web集群系统中多维调度因子的多目标函数．在此基础上提出了一种既适应网络访问特征，又支持QoS的Web集群调度算法．最后给出了其算法性能测试结果．     

A Data Cube Model for Prediction-Based Web Prefetching

Reducing the web latency is one of the primary concerns of Internet research. Web caching and web prefetching are two effective techniques to latency reduction. A primary method for intelligent prefetching is to rank potential web documents based on prediction models that are trained on the past web server and proxy server log data, and to prefetch the highly ranked objects. For this method to work well, the prediction model must be updated constantly, and different queries must be answered efficiently. In this paper we present a data-cube model to represent Web access sessions for data mining for supporting the prediction model construction. The cube model organizes session data into three dimensions. With the data cube in place, we apply efficient data mining algorithms for clustering and correlation analysis. As a result of the analysis, the web page clusters can then be used to guide the prefetching system. In this paper, we propose an integrated web-caching and web-prefetching model, where the issues of prefetching aggressiveness, replacement policy and increased network traffic are addressed together in an integrated framework. The core of our integrated solution is a prediction model based on statistical correlation between web objects. This model can be frequently updated by querying the data cube of web server logs. This integrated data cube and prediction based prefetching framework represents a first such effort in our knowledge.     

网络DDoS攻击流的小波分析与检测

将小波分析中的小波变换模极大方法用于检测分布式拒绝服务攻击引起的突发流量。在探讨如何运用小波模极大对突发流量进行判定的基础上,设计了一个检测突发攻击流量的方法,并对实际采集到的网络流量和仿真攻击流量的混合流作了计算机模拟验证。结果表明,当攻击流的突变幅度为正常流量的2倍￣3倍时,检测漏判率不超过5%;当攻击流的突变幅度提升为正常流量均值的3倍￣5倍时,检测漏判率不超过1%。攻击越强,检测漏判率越小。     

Implementation of hybrid P2P networking distributed web crawler using AWS for smart work news big data

Web crawlers collect and index the vast amount of data available online to gather specific types of objective data such as news that researchers or practitioners need. As big data are increasingly used in a variety of fields and web data are exponentially growing each year, the importance of web crawlers is growing as well. Web servers that currently handle high traffic, such as portal news servers, have safeguards against security threats such as distributed denial-of-service (DDoS) attacks. In particular, the crawler, which causes a large amount of traffic to the Web server, has a very similar nature to DDoS attacks, so the crawler’s activities tend to be blocked from the web server. A peer-to-peer (P2P) crawler can be used to solve these problems. However, the limitations with the pure P2P crawler is that it is difficult to maintain the entire system when network traffic increases or errors occur. Therefore, in order to overcome these limitations, we would like to propose a hybrid P2P crawler that can collect web data using the cloud service platform provided by Amazon Web Services (AWS). The hybrid P2P networking distributed web crawler using AWS (HP2PNC-AWS) is applied to collecting news on Korea’s current smart work lifestyle from three portal sites. In Portal A where the target server does not block crawling, the HP2PNC-AWS is faster than the general web crawler (GWC) and slightly slower than the server/client distributed web crawler (SC-DWC), but it has a similar performance to the SC-DWC. However, in both Portal B and C where the target server blocks crawling, the HP2PNC-AWS performs better than other methods, with the collection rate and the number of data collected at the same time. It was also confirmed that the hybrid P2P networking system could work efficiently in web crawler architectures.

     

集中管理式Web缓存系统及性能分析

共享缓存文件是减少网络通信量和服务器负载的重要方法，本文在介绍Web Caching技术及流行的Web缓存通信协议ICP的基础上，提出了一种集中管理式Web缓存系统，该系统通过将用户的HTTP请求，按照一定的算法分发到系统中某一合适的缓存服务器上，从而消除了缓存系统内部服务器之间庞大的通信开销及缓存处理负担，减少了缓存内容的冗余度．通过分析，证明了集中管理式Web缓存系统比基于ICP的简单缓存系统具有缓存效率高、处理开销低、延迟小等优点，并且该系统具有良好的可扩展性．     

应用层DDOS攻击检测技术研究

随着检测底层DDoS攻击的技术不断成熟和完善,应用层DDoS攻击越来越多。由于应用层协议的复杂性,应用层DDoS攻击更具隐蔽性和破坏性,检测难度更大。通过研究正常用户访问的网络流量特征和应用层DDoS攻击的流量特征,采用固定时间窗口内的请求时间间隔以及页面作为特征。通过正常用户和僵尸程序访问表现出不同的特点,对会话进行聚类分析,从而检测出攻击,经过实验,表明本检测算法具有较好的检测性能。     

Adaptive-level memory caches on World Wide Web servers

Owing to the fast growth of World Wide Web (WWW), web traffic has become a major component of Internet traffics. Consequently, the reduction of document retrieval latency on WWW becomes more and more important. The latency can be reduced in two ways: reduction of network delay and improvement of web servers’ throughput. Our research aims at improving a web server’s throughput by keeping a memory cache in a web server’s address space.In this paper, we focus on the design and implementation of a memory cache scheme. We propose a novel web cache management policy named the adaptive-level policy that either caches the whole file content or only a portion of it, according to the file size. The experimental results show three things. First, our memory cache is beneficial since, under our experimental workloads, the throughput improvement can achieve 32.7%. Second, our cache management policy is suitable for current web traffic. Third, with the increasing popularity of multimedia files, our policy will outperform others currently used in WWW.