一种基于LSTM神经网络的流量预测模型

在移动互联网时代,流量经营一直是运营商推广业务发展市场的最要举措。中国移动适时推出了"4G任我看"视频业务,很受广大用户的青睐。在业务推广之际,后来的流量分析与管理,需要进行有效支撑。为此,特提出一种基于LSTM神经网络的流量预测模型,该模型对用户使用某种业务的历史流量进行分析,进而建立该类业务的流量预测模型,通过历史业务流量、影响业务流量相关指标、时间等指标对业务未来流量进行预测。     

基于GAN和XGBoost融合的高精度业务流量识别方法

随着互联网技术的不断发展以及网络规模的不断扩大，新的网络业务层出不穷，为了保障用户服务质量，准确快速地对业务流量进行分类是目前的研究重点。传统业务识别方法多以协议或具体业务为分类依据，应用性较低。文章结合业务流量特征和机器学习方法，提出了一种基于生成对抗网络(GAN)和极端梯度增强(XGBoost)融合的业务流量识别方法。该方法首先提取代表业务资源需求的流量特征；然后通过改进GAN算法扩充少数类样本，解决业务识别过程中出现的数据集分布不平衡导致的模型准确率低的问题；最后通过随机森林算法进行特征选择，并利用XGBoost算法完成模型训练。结果表明，该方法对业务识别的准确率达到了97.32%。     

互联网+新秩序QoS在新时期IP网络中的应用

本文对互联网+时代业务流量需求和运营商带宽有限之间的矛盾进行了阐述,并就此问题提出了相应的Qo S解决方案。本文对Qo S的三种模型及实现原理进行了说明,结合互联网+时代各种业务类型特点,有针对性的对各种业务类型提出了Qo S解决建议,对运营商的流量精细化运营是一个很好的补充。     

对互联网流量分析技术研究

随着硬件设施的提高,电子计算机技术的进步,互联网得到了快速的普及,互联网几乎覆盖了各行各业。互联网业务越来越多,承载的业务量也是呈爆发式发展,这时就需要我们对互联网流量进行准确科学的测量和深入分析研究,制定科学的技术支持,拓展互联网应用潜力,缩减互联网流量成本。本文就此问题展开讨论,首先对我国目前的互联网流量应用的分析技术现状进行了深入分析,接着深入探讨了具体的技术解决方案。     

电信进入“全业务”时代视频网站何去何从？

视频业务吸引了互联网的大部分流量，未来，全业务电信运营商也将有可能在视频领域一展身手。     

流量客户价值挖掘探索研究

移动互联网时代,运营商的短信和语音等业务不断下滑,电信运营商大力推进流量经营。文章从通过对流量客户的分析得到流量业务精细化运营方式,提高了流量业务推荐办理的精准度。     

互联网流量成分及运营策略分析

本文从互联网运营商的视角, 通过对互联网流量成分的统计分析,找出了互联网流量成分近年来的发展变化趋势,并且从网络运营管理的角度提出如何对流量实施必要的管理,制定适应当前网络流量特点的业务模式。     

移动互联网流量运营模式及策略研究

移动互联网时代的到来,为电信运营商带来了机遇,同时也伴随着挑战。本文分析电信增值业务的运营现状和互联网业务的发展,从精细化运营角度,对提升流量的运营策略进行了分析和研究。     

一种基于业务分类的大规模用户高速流量监控策略

随着互联网承载业务的多样化,对互联网的可管、可控提出了更高的要求,本文对基于下一代大规模用户接入环境的流量监控问题展开研究,提出了一种基于用户业务分类的大规模用户高速流量监控策略,该策略可以满足10 Gbit/s速率下960个用户的并发流量监控需求.     

互联网运营支撑系统建设思路研究

随着大数据时代背景的到来,实时监听网络运行与流量动向,准确掌握管道内容与趋势,最终实现用户可识别、业务可区分、流量可调控、网络可管理。本文通过对互联网运营支撑系统建设思路研究,通过对互联网领域的用户、业务、内容等方面的信息识别,以助力公司提升精准化营销服务、互联网业务开展、行业信息服务、互联网产业链把控等核心能力,实现用户、内容、业务、终端、资费及管道的流量经营。     

运营商互联网流量监测需求探讨

分析了运营商对互联网流量监测、分析的需求，并简要介绍流量监测分析系统的构成和产品发展状况，提出了系统的发展建议。     

Internet performance monitoring

The growing diversity of services in the Internet is motivating research to improve measurability of traffic and Internet performance. This paper surveys current projects and tools for Internet performance monitoring, ranging from passive router-based traffic flow measurement methods to large-scale active performance monitoring projects. The tools and methods are discussed according to their protocol layer, starting from the network layer (ATM, MPLS) to IP/ICMP and transport/application layers. At each protocol layer the strengths and limitations of the methods are highlighted. Finally, issues and challenges for future research are reviewed     

基于云计算的海量网络流量数据分析处理研究

随着互联网技术的迅速发展,在我们的生活中网络已经成为我们不可以缺少的重要的组成部分.网络流量监控技术是对网络中海量的流量数据进行分析的重要工具和技术.基于云计算的网络流量监控技术可以对网络流量数据和用户的特征进行更好的分析,可以对用户的上网行为进行深入的挖掘,更好的为用户推荐喜欢的网络内容.本文结合互联网的发展现状对海量网络流量数据分析技术进行了分析,在基于云计算的基础上提出了海量网络流量数据分析的几个关键性技术,对基于云计算的海量网络流量数据分析技术进行了分析和研究.     

Wide-area Internet traffic patterns and characteristics

The Internet is rapidly growing in number of users, traffic levels, and topological complexity. At the same time it is increasingly driven by economic competition. These developments render the characterization of network usage and workloads more difficult, and yet more critical. Few recent studies have been published reporting Internet backbone traffic usage and characteristics. At MCI, we have implemented a high-performance, low-cost monitoring system that can capture traffic and perform analyses. We have deployed this monitoring tool on OC-3 trunks within the Internet MCI's backbone and also within the NSF-sponsored vBNS. This article presents observations on the patterns and characteristics of wide-area Internet traffic, as recorded by MCI's OC-3 traffic monitors. We report on measurements from two OC-3 trunks in MCI's commercial Internet backbone over two time ranges (24-hour and 7-day) in the presence of up to 240,000 flows. We reveal the characteristics of the traffic in terms of packet sizes, flow duration, volume, and percentage composition by protocol and application, as well as patterns seen over the two time scales     

基于车联网的交通流云处理平台研究

Internet of Car, resulting from the Internet of Things , is a key point for the forthcoming smart city. In this article, GPS technology, 3G wireless technology and cloudprocessing technology are employed to construct a cloudprocessing network platform based on the Internet of Car. By this platform, positions and velocity of the running cars , information of traffic flow from fixed monitoring points and transportation videos are combined to be a virtual traffic flow data platform, which is a parallel system with real traffic flow and is able to supply basic data for analysis and decision of intelligent transportation system.     

利用NetFlow技术构建网络异常监测及分析系统

随着互联网的不断普及,网络已经跟人们的日常生活密不可分,使用者在享受网络所带来的便利的同时,网络上的许多问题也陆续衍生而出,运营商网络正面临着日益严重的安全威胁.作为网络管理者,如何迅速有效地监测网络异常情况,同时准确地掌握整个网络的业务流量模型,供市场部门作决策分析,已成为一项重要的课题.介绍了利用NetFlow技术,构建网络异常监测及分析系统,利用本系统可随时监测网络运行情况,以达到网络稳定顺畅运作及节省经费、人力的目的.     

互联网视听节目监测从业人员上网行为审计系统设计与实现

文章根据互联网视听节目监测从业人员的工作内容,提出上网行为审计系统的设计并加以实现,系统满足加强互联网信息安全的需求,同时规范上网行为、提高工作效率。系统通过用户准入、上网行为记录、流量控制、终端管理等技术手段,部署了一套完整的上网行为审计系统。本系统旨在解决互联网视听节目监测从业人员访问互联网所衍生的信息安全隐患、工作效率低等问题。     

Efficient reactive monitoring

Networks are monitored in order to ensure that the system operates within desirable parameters. The increasing complexity of networks and services provided by them increases this need for monitoring. Monitoring consists of measuring properties of the network, and of inferring an aggregate predicate from these measurements. Conducting such monitoring introduces traffic overhead that may reduce the overall effective throughput. This paper studies ways to minimize the monitoring communication overhead in IP networks. We develop and analyze several monitoring algorithms that achieve significant reduction in the management overhead while maintaining the functionality. The main idea is to combine global polling with local event driven reporting. The amount of traffic saving depends on the statistical characterization of the monitored data. We indicate the specific statistical factors that affect the saving and show how to choose the right algorithm for the type, of monitored data. In particular, our results show that for Internet traffic our algorithms can save more than 90% of the monitoring traffic     

基于5G的车联网体系架构及其应用分析

文中立足于车联网及移动通信技术的发展情况,简略阐述了研究背景,介绍了基于5G移动通信技术的车联网体系架构,并以我国某智慧园区为例,从智慧路况监测、远程驾驶、高精度定位、车联网业务平台主系统以及交通信号优化等方面着手,对其应用实例进行了详细分析,旨在为相关研究人员提供参考。     

A novel traffic identification approach based on multifractal analysis and combined neural network

An accurate identification of Internet traffic of different applications is highly relevant for a broad range of network management and measurement tasks, including traffic engineering, service differentiation, performance monitoring, and security. Traditional traffic identification approaches have become increasingly inaccurate due to restrictions of port numbers, protocol signatures, traffic encryption, and etc. In this paper, a new traffic identification approach based on multifractal analysis of wavelet energy spectrum and classification of combined neural network models is proposed. The proposed approach is able to achieve the identification of different Internet application traffic by performing classification over the wavelet energy spectrum coefficients that were inferred from the original traffic. Without using any payload information, the proposed approach has more advantages over traditional methods. The experiment results illustrate that the proposed approach has satisfactory identification results.