P2P流量识别与管理技术

P2P流量在推动Internet宽带化的同时也带来了资源过度占用和网络安全等问题.本文调查和研究了P2P流量识别和策略控制的最新技术及相关设备,总结出P2P流量综合控制模型,并指出进一步的研究方向.     

基于主动识别技术的网关P2P流量检测

P2P流量在对Internet起巨大推动作用的同时,也带来了因资源过度占用而引起的网络拥塞以及安全隐患等问题,妨碍了正常网络业务的开展.文中介绍了目前主流的网关P2P流量检测技术并分析了这些技术的优缺点,提出了一种基于主动识别技术来检测和控制P2P流量的方法,以便对P2P流量进行识别和有效控制.     

P2P流量识别方法的研究及实现

近年来,网络新技术层出不穷,有对等网络、VoIP．P2P流媒体等。IPv4网络是一个“尽力而为”的网络,主要提供数据业务服务,对P2P流等非传统数据业务的应用则显出很多无奈,QoS是无保证的。P2P网络“带宽吞噬”特性造成了网络带宽的巨大消耗,甚至会引起网络拥塞,大大降低了网络性能,劣化了网络服务质量。因此对P2P流量进行识别和控制是解决问题的关键。首先介绍了P2P流量识别方法,分析了它们的优缺点;然后提出一种基于流传输特性的P2P流量识别模型,此模型的创新点在于不要检测数据净荷就可以识别P2P流量,提高了识别的效率;最后对P2P流量识别模型进行了分析。     

P2P流量疏导与优化

针对目前P2P应用的普及,对互联网带宽的占用情况越来越严重的问题,介绍了吉林联通利用P2P流量疏导与优化系统,运用先进的P4P技术和创新模式,有效缓释电信运营商迅猛增长的P2P应用流量压力问题,并最终使得运营商具备对P2P流量和业务进行有效监控、管理和运营的能力。     

P2P流量检测技术与分析

P2P技术及其应用的快速发展增加了网络的负载,影响了网络的性能,因此,对P2P流量进行分析及控制十分必要。在介绍P2P流量检测技术的基础上,对目前几种主流P2P流量识别技术进行比较和分析,指出了各种技术的优势和不足,阐明了流量检测技术的发展方向,提出了一种将不同检测方法相结合以满足一定准确率和效率的思路。     

P2P流量优化技术综述

P2P应用对网络带宽的过度消耗给网络运营商带来了越来越大的压力。如何有效地控制P2P流量,既能够提高承载网的效率又能够保护用户的利益,是互联网产业界和学术界广泛关注的问题。各种P2P流量优化技术的提出正是为了解决上述问题。本文在指出了P2P流量优化技术的必要性之后,介绍了P2P流量优化技术的发展现状,包括一些最新的P2P流量优化方案和P2P流量优化技术标准制定的进展情况．并给出了相应的观点与看法。     

新疆广电数据网络P2P数据流量分析与控制

P2P应用的大量出现对运营商的网络架构、运营模式、价值链等都产生了很大影响。本文以新疆广电为例,对P2P技术及其对新疆广电网络的影响进行了概述,对P2P流量在空间和时间上的特性进行了说明,对P2P流量分析技术、控制技术以及解决方案进行了论述,最后提出应当采用疏堵结合的方法实现广电宽带数据网络P2P控制的解决方案。     

基于P2PCache的P2P流量优化技术

介绍了P2PCache技术的工作原理,Cache系统的评估方法,基于P2PCache的P2P流量优化方案．以及P2PCache为运营商带来的益处和风险。     

校园网P2P流量监控技术分析

随着P2P业务在校园中的广泛应用,校园网络的质量受到了前所未有的挑战,如何有效地监控P2P应用已经成为校园网络管理的重点之一。文章分析了P2P应用对校园网网络流量的影响,提出了如何在校园网中有效地识别和控制P2P流量,并对这些识别和控制的方法分别进行了比较。     

基于DPI的P2P流量控制系统的设计与实现

基于对P2P通信进行控制的迫切需求,论文给出了一种基于DPI的P2P流量控制系统的设计与实现。首先描述了识别P2P通信的一些技术,在此基础上,对P2P流量综合控制模型进行了分析;再结合实际情况给出了一种基于DPI的流量控制模型,并给出了其简单实现;最后对该模型进行了性能分析和评价。实验证明,该实现对于控制P2P流量是非常有效的。     

P2P network traffic control mechanism based on global evaluation values

Peer-to-peer (P2P) computing technology has been widely used on the Internet to exchange data. However, it occupies much network bandwidth, and thus greatly influences traditional business on the Interact. Besides, problems about free-riders and 'tragedy of the commons' in the P2P environment estrange from it P2P users who constantly contribute to the network with quality resources. This article proposes a new P2P network traffic control mechanism based on global evaluation values. It aims to help individual users to avoid peak traffic time as much as possible, ease network congestion and protect traditional business on the Interact, as well as differentiating priority grades of peers according to their contributions and stimulating them to share their valuable resources actively. This article first analyzes the current state of network traffic, and then elaborates on P2P network traffic control policies and proposes the peer's priority level differentiation mechanism based on global evaluation values. Finally,after the testing results and analysis of the proposed P2P network traffic control mechanism are discussed, conclusions are drawn.     

P2P流量管理技术研究

近年来,P2P(peer-to-peer)技术的应用类型、用户规模和网络流量均呈爆发式增长,但P2P应用的兴起,也打破了网络运营商原有的运营和商业模式.为了更好地管理P2P流量,业界进行了多层次的探索,主要包括:一是通过DPI(深度数据包检测)技术进行流量识别和管控,二是进行流量本地化的优化,其中P2P缓存与Peer选择优化是两个主要方向.基于对上述技术的分析,本文提出一种将P2P缓存技术与Peer选择优化技术相结合的P2P承载架构,并以此承载架构为基础,对用户的管理、认证、计费、安全进行综合考虑,从而实现电信级的P2P分发网络.     

Identifying file-sharing P2P traffic based on traffic characteristics

This article focuses on identifying file-sharing peer-to-peer （P2P） （such as BitTorrent （BT）） traffic at the borders of a stub network. By analyzing protocols and traffic of applications, it is found that file-sharing P2P traffic of a single user differs greatly from traditional and other P2P （such as QQ） applications＇ traffic in the distribution of involved remote hosts and remote ports. Therefore, a method based on discreteness of remote hosts （RHD） and discreteness of remote ports （RPD） is proposed to identify BT-like traffic. This method only relies on flow information of each user host in a stub network, and no packet payload needs to be monitored. At intervals, instant RHD for concurrent transmission control protocol and user datagram protocol flows for each host are calculated respectively through grouping flows by the stub network that the remote host of each flow belongs to. On given conditions, instant RPD are calculated through grouping flows by the remote port to amend instant RHD. Whether a host has been using a BT-like application or not can be deduced from instant RHD or average RHD for a period of time. The proposed method based on traffic characteristics is more suitable for identifying protean file-sharing P2P traffic than content-based methods Experimental results show that this method is effective with high accuracy.     

城域数据网P2P流量优化方案

分析了P2P流量在城域数据网中的流向,并从运营商网络建设的角度,提出了P2P流量优化方案,包括BRAS节点的分布部署、IPv6地址的加速引入、分布式地址转换技术的应用和对P4P技术的关注,为运营商在智能管道时代在流量管理方面获得主动。     

基于UDP流量的P2P流媒体流量识别算法研究

以几款主流的P2P流媒体网络电视作为研究对象,深入分析了其产生的流量在端口使用方面的特点和报文长度分布上的差异。通过对这些特征的总结和提取,获得了基于端口特性“在一次交互过程中,特定主机的特定端口唯一确定一种应用”等结论。在此基础上提出了一种基于带有扩展属性的流记录准确识别P2P应用UDP流量的EXID算法。通过对CERNET江苏省边界10G主干信道上采集的Trace数据中5种P2P流媒体应用进行识别,并与机器学习流量识别算法进行比较,其结果表明提出的方案具有很高的查准率和查全率,时间效率高,且不易受样本比重的影响。     

An efficient method of P2P traffic identification based on wavelet packet decomposition and kernel principal component analysis

Peer‐to‐peer (P2P) traffic identification is currently an important challenge to network management and measurement. Many approaches based on statistics have been proposed to identify P2P traffic. However, flow features extracted by traditional methods are rough and one‐sided, which might lead to inaccuracy identification of network traffic. Besides, P2P traffic has too many statistical features, which is a challenge to the time complexity and space complexity of the classifier. This work focuses on the study of flow features. First, micro features of flow signals are extracted based on wavelet packet decomposition, and we combine them with the traditional features into combination features. The experimental results show that combination features have better performance than traditional features for P2P traffic identification, and 16 kinds of wavelet functions were tested to find the best one. Second, a feature reduction algorithm based on improved kernel principal component analysis is provided. The results show that the feature reduction algorithm proposed in this paper plays good performance to P2P traffic identification, because it could greatly reduced the number of features while having no affection on identification accuracy. Copyright © 2012 John Wiley & Sons, Ltd.     

高速网络环境下的P2P流媒体业务分析和识别方法

The growing P2P streaming traffic brings a variety of problems and challenges to ISP networks and service providers.A P2P streaming traffic classification method based on sampling technology is presented in this paper.By analyzing traffic statistical features and network behavior of P2P streaming,a group of flow characteristics were found,which can make P2P streaming more recognizable among other applications.Attributes from Netflow and those proposed by us are compared in terms of classification accuracy,a...     

P2P流量识别和管控技术分析

基于P2P模式的业务和应用给互联网的发展带来了巨大影响,本文在简要分析了现网中P2P流量分布类型的基础上,重点探讨了互联网P2P流量的三种识别检测技术和两种流量管控技术,给出了对P2P流量管控技术的运营选用建议。