Virtual Private/Overlay Network Design With Traffic Concentration and Shared Protection

In this paper different algorithms are presented and evaluated for designing Virtual Private/Overlay Network (VPNs/VONs) over any network that supports resource partitioning e.g. ATM (Asynchronous Transfer Mode), MPLS (Multi Protocol Label Switching), or SDH/SONET (Synchronous Digital Hierarchy/Synchronous Optical Networking). All algorithms incorporate protection as well. The VPNs/VONs are formed by full mesh demand sets between VPN/VON endpoints. The service demands of VPNs/VONs are characterized by the bandwidth requirements of node-pairs (pipe-model).We investigated four design modes with three pro-active path based shared protection path algorithms and four heuristics to calculate the pairs of paths. The design mode determines the means of traffic concentration. The protection path algorithms use Dijkstras shortest path calculation with different edge weights. The demands are routed one-by-one, therefore the order in which they are processed matters.To eliminate this factor we used three heuristics (simulated allocation, simulated annealing, threshold accepting). We present numerical results obtained by simulation regarding the required total amount of capacity, the number of reserved edges, and the average length of paths.Péter Hegyi received MSc (2004) degree from the Budapest University of Technology and Economics, Hungary, where he is currently a PhD student at the Department of Telecommunications and Media Informatics. His research interests focus on design of intra- and inter-domain multilayer grooming networks and routing with protection. He has been involved in a few related projects (IKTA, ETIK, NOBEL).Markosz Maliosz is a researcher in the High Speed Networks Laboratory, Department of Telecommunication and Media Informatics at the Budapest University of Technology and Economics, where he received his MSc degree in Computer Science (1998). He has participated in projects concerning telecommunication services, network device control, Voice and Video over IP. His current research areas are Virtual Private Networking and traffic engineering in optical networks.Ákos Ladányi is a student at the Department of Telecommunications and Media Informatics at the Budapest University of Technology and Economics. His research interests focus on routing, network resilience, and combinatorial optimization.Tibor Cinkler has received MSc(94) and PhD(99) degrees from the Budapest University of Technology and Economics, Hungary, where he is currently Associate Professor at the Department of Telecommunications and Media Informatics. His research interests focus on routing, design, configuration, dimensioning and resilience of IP,MPLS, ATM, ngSDH and particularly of WR-DWDMbased multilayer networks. He is the author of over 60 refereed scientific publications and of 3 patents.     

Partition-Based Online Aggregation with Shared Sampling in the Cloud

Online aggregation is an attractive sampling-based technology to response aggregation queries by an estimate to the final result, with the confidence interval becoming tighter over time. It has been built into a MapReduce-based cloud system for big data analytics, which allows users to monitor the query progress, and save money by killing the computation early once sufficient accuracy has been obtained. However, there are several limitations that restrict the performance of online aggregation generated from the gap between the current mechanism of MapHeduce paradigm and the requirements of online aggregation, such as： 1） the low sampling efficiency due to the lack of consideration of skewed data distribution for online aggregation in MapReduce, and 2） the large redundant I/O cost of online aggregation caused by the independent job execution mechanism of MapReduce. In this paper, we present OLACloud, a MapReduce-based cloud system to well support online aggregation for different data distributions and large-scale concurrent query processing. We propose a content-aware repartition method with a fair-allocation block placement strategy to increase the sampling efficiency and guarantee the storage and computation load balancing simultaneously. We also develop a shared sampling method to share the sampling opportunities among multiple queries to reduce redundant I/O cost. We also implement OLACloud in Hadoop, and conduct an extensive experimental study on the TPC-H benchmark for skewed data distribution. Our results demonstrate the efficiency and effectiveness of OLACloud.     

Demand-wise Shared Protection for Meshed Optical Networks

In this paper, a new shared protection mechanism for meshed optical networks is presented. Significant network design cost reductions can be achieved in comparison to the well-known 1+1 protection scheme. Demand-wise Shared Protection (DSP) is based on the diversification of demand routings and exploits the network connectivity to restrict the number of backup lightpaths needed to provide the desired level of protection. Computational experiments illustrate the benefits of the DSP concept for cost efficient optical network designs.Arie M. C. A. Koster studied technical mathematics at Delft University of Technology, The Netherlands. His PhD thesis (University Maastricht, The Netherlands, 1999) deals with models and algorithms for frequency assignment in wireless networks. Currently, he is a researcher at the Zuse Institute Berlin (ZIB). His research interests are in mathematical optimization, algorithmic graph theory, and telecommunciation network design.Adrian Zymolka studied mathematics at the Philipps University in Marburg, Germany. Since 1999, he has been a research assistant at the Zuse Institute Berlin (ZIB) and works on mathematical optimization in telecommunications. His research focuses on the cost efficient design of survivable optical networks.Monika Jäger has been a senior scientist in the department of Photonic Networks and Network Architecture at T-Systems, Technologiezentrum in Berlin since 1998. She held previous positions with the Fraunhofer Institute for Open Communication Systems, and DeTeWe. In 1992, She graduated in Electrical Engineering fromMunich University of Technology,Germany.Her current research interests are in the area of optical transport network design.RalfHälsermann has been a junior research engineer in the department of PhotonicNetworks and Network Architecture at T-Systems Technologiezentrum in Berlin since August 2001. He graduated in 2001 from Deutsche Telekom AG, University of Applied Sciences, Leipzig, Germany. He is currently working on protection and restoration issues in optical networks.     

一种高速流量聚合方法的设计与实现

本文运用数据仓库原理,设计了一套基于NetFlow的高速流量分级聚合方法.基于四个时间粒度将原始数据进行聚合处理并转存到数据库,达到对高速网络环境下的海量流量数据进行有效缩减和归并整理的目的,同时,结合对细节级数据的压缩处理策略,提高了流量分析的效率.流量聚合处理采用多线程技术加以实现,提高系统性能.     

动态共享库保护方法研究

引入动态共享库机制能节约内存资源,并容易升级,但却带来安全隐患。针对该问题,研究动态链接机制,提出一种针对动态共享库的程序运行时监控和保护的方法。对共享库文件进行签名和验证,并对库函数调用实行监控。实验结果显示,该方法对于动态共享库的几种常见攻击方法有较好的防御作用。     

基于特征聚类的路由器异常流量过滤算法

基于当前入侵检测技术在检测到攻击的情况下没有良好的反应策略过滤攻击流量这一问题,提出了基于攻击流量特征聚类的特征提取算法AFCAA(anomaly traffic character aggregation algorithm).针对一般DOS(denial ofservice)/DDOS(distributed denial ofservice)攻击流数据包头中具有某些相似的特性,AFCAA通过运用重心原理进行统计聚类,在一定的欧氏距离范围内对基于目的IP的攻击流样本相应字段进行聚类划分,动态地提取出攻击流的重心作为攻击的特征.然后,及时地把其特征传输给Net Filter,可以进行高效的过滤,并保护正常流量的传输.实验结果表明,对当前流行的多种拒绝服务攻击,应用AFCAA系统的软件路由器都能够较准确地获取异常流量的特征,从而有效地进行过滤,减少攻击包传播的危害,保护有限的网络资源.     

路由器端基于模式聚集的流量控制研究

不断发展的DoS/DDoS攻击对Internet安全是一个严重的威胁,传统的IDS针对DoS/DDoS攻击的防御方法并不能减少路由器上的攻击流量.文中提出了一种新的运行在核心路由器上的基于多层模式聚集的流量控制机制,它根据不同协议的统计特征设计出不同聚集模式,使用轻量级的协议分析和多层聚集来控制流量.实验证明该机制不但简化了包分类的复杂性,对攻击手段的变化还有一定的免疫性,能对恶意攻击包进行有效过滤,实现在骨干网络上限制非法流量的目的.     

路由器端基于模式聚集的流量控制研究

不断发展的DoS/DDoS攻击对Internet安全是一个严重的威胁,传统的IDS针对DoS/DDoS攻击的防御方法并不能减少路由器上的攻击流量。文中提出了一种新的运行在核心路由器上的基于多层模式聚集的流量控制机制,它根据不同协议的统计特征设计出不同聚集模式,使用轻量级的协议分析和多层聚集来控制流量。实验证明该机制不但简化了包分类的复杂性,对攻击手段的变化还有一定的免疫性,能对恶意攻击包进行有效过滤,实现在骨干网络上限制非法流量的目的。     

基于隐私保护的非线性安全数据融合方案

数据融合能减少无线传感器节点中传输的冗余信息量,节省传感器的能量消耗和通信带宽。而无线传感器网络由于部署的环境和自身的特点使得在数据融合过程中的隐私信息易受到各种威胁。为了减少信息传输过程中的冗余信息和保护数据融合过程中的隐私信息安全,文中通过对经典安全数据融合方案ESPDA进行改进,提出一种基于隐私保护的非线性安全数据融合方案,方案先生成模式码确定上传节点后再进行非线性融合,使其在实现数据融合隐私保护的同时能够在一定程度上减少能耗。仿真结果表明,它不仅能够有效地消除冗余数据的传输,减少能耗,而且还能保证数据安全完整地传输至融合节点。     

STGSA: A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction

The success of intelligent transportation systems relies heavily on accurate traffic prediction, in which how to model the underlying spatial-temporal information from traffic data has come under the spotlight. Most existing frameworks typically utilize separate modules for spatial and temporal correlations modeling. However, this stepwise pattern may limit the effectiveness and efficiency in spatial-temporal feature extraction and cause the overlook of important information in some steps.Furthe...     

共享软件的硬盘序列号保护机制的实现

共享软件通常都采用注册用户产生注册码的保护方法,但是传统的保护方法常采用“用户名”和“注册码”对应的机制。由于这种方法安全性极差,该文提出一种采用读取所装计算机硬盘序列号作为保护原码元素的方式,大大提高了共享软件的合法使用的安全性。     

IP RAN中流量工程保护技术分析

随着3G/LTE网络的不断演进和发展,运营商对下一代移动回程网的可靠性提出了更高的要求,即要求具备业务端到端保护(接入、汇聚、核心层任何节点的电信级保护)。IP RAN是当前移动承载网领域主流的解决方案,它采用TE(流量工程)保护技术,用于提高网络运作效率与可靠性,并优化网络资源利用率和流量性能。本文就流量工程的两种保护技术进行了分析和比较。     

基于业务的信息安全等级保护风险评估方法

文章通过对组织业务进行分析,根据组织的业务识别出重要的资产,提出一种基于业务的信息资产识别和评估方法,为等级保护的定级、测评和整改等工作提供科学的参考依据。     

差分隐私保护的Android应用流量行为混淆方法

针对Android用户在终端传输数据和发送信息所带来的网络应用行为暴露等问题,通过结合自定义流量混淆和差分隐私无关流量干扰两种方法的优势,能够在保证Android应用网络连接状态和数据传输内容不变的前提下,通过改变流量数据包的时序和数目特征,达到对指定用户应用行为特征的隐私保护。实验结果表明,选取Android典型应用流量并提取六种主要流量特征,对比混淆前后数据包特征,所提混淆方法能够有效地改变Android终端的应用流量,抵御支持向量机（Support Vector Machine,SVM）和BP（Back Propagation）神经网络算法的识别,准确率高达96.55%,最终实现对Android终端应用行为的保护。     

Environmental Protection in Scenic Areas: Traffic Scheme for Clean Energy Vehicles Based on Multi-agent

The low-carbon environmental protection and traffic congestion are two primary issues that people focus on highly and need to be solved efficiently. Under the circumstance, this paper designs a transportation simulation system for clean energy vehicles in scenic area based on multi-agent. From the view of introducing clean energy electric vehicles with limited funds and unlimited funds, we investigate the optimal introduction scheme and the optimal traffic scheme of clean energy vehicles to alleviate air pollution and tourist overcrowding. Combined with the specific circumstances of a famous scenic spot in China, we conduct the simulation and propose many countermeasures and suggestions to improve traffic scheme of clean energy vehicles.