Analysis and modelling of traffic produced by adaptive HTTP-based video

The increase of HTTP-based video popularity causes that broadband and Internet service providers’ links transmit mainly multimedia content. Network planning, traffic engineering or congestion control requires an understanding of the statistical properties of network traffic; therefore, it is desirable to investigate the characteristic of traffic traces generated by systems which employ adaptive bit-rate streaming. Our first contribution is an investigation of traffic originating from 120 client-server pairs, situated in an emulated content distribution network, and multiplexed onto a single network link. We show that the structure of the traffic is distinct from the structure generated by the first and second generation of HTTP video systems, and furthermore, not similar to the structure of general Internet traffic. The obtained traffic exhibits negative and positive correlations, anti-persistence, and its distribution function is skewed to the right. Our second contribution is an approximation of the traffic by ARIMA/FARIMA processes blue and artificial neural networks. As we show, the obtained traffic models are able to enhance the performance of an adaptive streaming algorithm.     

自相似网络业务的一个FARIMA模型

近来发现,高速网络业务具有自相似及长相关特性,分数噪声可描述该类业务。但它仅表现长相关特性,给出了利用ＦＡＲＩＭＡ模型拟合自似网络业务的一整套方法,该模型同时刻画了实际业务的长相关与短相关行性,通过对实测数据的实验, 模型的优效性。     

Framework based on stochastic L-Systems for modeling IP traffic with multifractal behavior

This paper presents and compares a set of traffic models, and associated parameter fitting procedures, based on so-called stochastic L-Systems, which were introduced by biologist A. Lindenmayer as a method to model plant growth. Starting from an initial symbol, an L-System generates iteratively sequences of symbols, belonging to an alphabet, through successive application of production rules. In a traffic modeling context, the symbols are interpreted as packet arrival rates or mean packet sizes, and each iteration is associated to a finest time scale of the traffic. These models are able to capture the multiscaling and multifractal behavior sometimes observed in Internet traffic. We describe and compare four traffic models, one characterizing the packet arrival process, and the other three characterizing both the packet arrival and the packet size processes. The models are tested with several measured traffic traces: the well-known pOct Bellcore, a trace of aggregate WAN traffic and two traces of specific applications (Kazaa and Operation Flashing Point). We assess the multifractality of these traces using Linear Multiscale Diagrams. The traffic models are evaluated by comparing, for the measured traffic and for traffic generated according to the inferred models, the probability mass function, the autocovariance function and the queuing behavior. Our results show that the L-System based traffic models that characterize both the packet arrival and packet size processes can achieve very good fitting performance in terms of first- and second-order statistics and queuing behavior.     

基于FARIMA模型的Internet网络业务预报

最近的网络研究发现Internet网络业务同时呈现长相关和短相关特性,因此建立可以同时描述,预报长相关和短相关特性的网络业务模型很有必要。文中给出了利用FARIMA模型进行建模和预报的方法,实验表明这种方法用于实际Internet网络trace是非常有效的,另外提供了简化FARIMA模型拟合的方法和具体步骤,这样大大缩短了模型辨识的时间,对于实际网络预报有很好的实用性。     

Criticisms of modelling packet traffic using long-range dependence (extended version)

This paper criticises the notion that long-range dependence is an important contributor to the queuing behaviour of real Internet traffic. The idea is questioned in two different ways. Firstly, a class of models used to simulate Internet traffic is shown to have important theoretical flaws. It is shown that this behaviour is inconsistent with the behaviour of real traffic traces. Secondly, the notion that long-range correlations significantly affects the queuing performance of traffic is investigated by destroying those correlations in real traffic traces (by reordering). It is shown that the longer ranges of correlations are not important to mean queue length except in one case with an extremely high load.     

基于FARIMA的ARP欺骗入侵检测

针对ARP网络流量具有自相似性,ARP欺骗会导致ARP网络流量局部突发的特征,在进行理论分析的基础上,提出一种ARP欺骗入侵检测方法。采用适合描述自相似性的FARIMA准确预测ARP网络流量,在线实时计算每个周期实测值和预测值的差值,比较差值变化率快速准确实现ARP欺骗入侵检测。运行结果证明FARIMA具有先进性,该方法可有效提高ARP欺骗实时入侵检测的检测率,实现追踪ARP欺骗攻击源主机。     

基于超爱尔兰分布的自相似网络排队模型研究

现有网络的业务流研究表明,多种通信业务中普遍存在自相似特性,但是如何对自相似业务流进行建模和分析一直是个难解问题。基于超爱尔兰拟合算法,建立了到达为泊松分布,服务时间为超爱尔兰分布的M/HErD/1/K自相似排队模型,推导得到呼叫损失概率、平均排队队长等排队性能的解析解。在实际业务环境下和传统的M/M/1/K排队模型进行了仿真对比,结果表明M/HErD/1/K模型不仅可有效表征业务流的快挂业务特性,而且能仿真出该网络在业务负荷较重时潜在的运营风险,对实际网络运营管理具有重要的指导作用。     

Dynamic admission control in hybrid QoS networks with WiFi access

Recent developments in the IEEE 802.11 standardizations[1] have been successful to offer high-speed data services. Hence, traffic classes (e.g. VoIP or video-conference) with different QoS requirements will be provided in future wireless LANs (WLAN). Sinc…     

Resource allocation for multimedia traffic flows using rate variance envelopes

In order for networks to support the delay and loss requirements of interactive multimedia applications, resource management algorithms are needed that efficiently allocate network resources. In this paper, we introduce a new resource allocation scheme based on rate variance envelopes. Such envelopes capture a flow's burstiness properties and autocorrelation structure by characterizing the variance of its rate distribution over intervals of different length. From this traffic characterization, we develop a simple and efficient resource allocation algorithm for static priority schedulers by employing a Gaussian approximation over intervals and considering a maximal busy period. Our approach supports heterogeneous quality-of-service requirements via our consideration of prioritized service disciplines, and supports heterogeneous and bursty traffic flows via our general framework of traffic envelopes. To evaluate the scheme, we perform trace-driven simulation experiments with long traces of compressed video and show that our approach is accurate enough to capture most of the available statistical multiplexing gain, achieving average network utilizations of up to 90% for these traces and substantially outperforming alternate schemes.     

Identification of adaptive video streams based on traffic correlation

Due to the popularity of Dynamic Adaptive Streaming Over HTTP (DASH), broadband and Internet service providers’ links transmit mainly multimedia content. As the most popular providers encrypt their video services, the attempts to identify their traffic through Deep Packet Inspection (DPI) encounter difficulties. Therefore, encrypted DASH traffic requires new classification methods. In this work, we propose to identify DASH traffic taking into account statistical dependencies among video flows. For this purpose, we employ cluster analysis which can identify groups of traffic flows that show similarity using only the application level information. In our work, we applied three unsupervised clustering algorithms, namely MinMax K-Means, OPTICS and AutoClass, to classify video traces obtained from an emulated environment. The experimental results show that the employed algorithms are able to effectively distinguish video flows generated by different play-out strategies. The classification performance depends on the network conditions and parameters of the learning process.

     

基于FARIMA的网络建模与性能分析

给出了利用FARIMA模型进行建模、拟合实际网络流量的方法和参数估计的具体步骤,研究了长短相关对网络性能的影响.研究结果表明,不论长相关还是短相关,FARIMA模型对实际业务拟合二者都非常接近,当缓存较小时,网络性能将由短相关特性支配,而且随着缓存增加,长相关业务下系统性能的衰减要比短相关业务下衰减的慢,这些发现对今后网络设计性能研究具有重要的参考价值.     

On the time scales in video traffic characterization for queueing behavior

To guarantee quality of service (QoS) in future integrated service networks, traffic sources must be characterized to capture the traffic characteristics relevant to network performance. Recent studies reveal that multimedia traffic shows burstiness over multiple time scales and long range dependence (LRD). While researchers agree on the importance of traffic correlation, there is no agreement on how much correlation should be incorporated into a traffic model for performance estimation and dimensioning of networks.In this article, we present an approach for defining a relevant time scale for the characterization of VBR video traffic in the sense of queueing delay. We first consider the Reich formula and characterize traffic by the Piecewise Linear Arrival Envelope Function (PLAEF). We then define the cutoff interval above which the correlation does not affect the queue buildup. The cutoff interval is the upper bound of the time scale which is required for the estimation of queue size and thus the characterization of VBR video traffic. We also give a procedure to approximate the empirical PLAEF with a concave function; this significantly simplifies the calculation in the estimation of the cutoff interval and delay bound with little estimation loss.We quantify the relationship between the time scale in the correlation of video traffic and the queue buildup using a set of experiments with traces of MPEG/JPEG-compressed video. We show that the critical interval, i.e. the range for the correlation relevant to the queueing delay, depends on the traffic load: as the traffic load increases, the range of the time scale required for estimation for queueing delay also increases. These results offer further insights into the implication of LRD in VBR video traffic.     

Adaptive scene-detection algorithm for VBR video stream

Several scene-detection algorithms, which are only based on bit rate fluctuations, have been proposed. All of them are presented on the fixed thresholds, which are obtained by the empirical records of the video characteristics. Due to the sensitivity of these methods to the accuracy of the records, which are generally obtained by testing several values repeatedly, bad performance evaluation might be observed for the actual scene detection, especially for real-time video traffic. In this paper, we review the previous works in this area, and study the correlation between the scene duration and the scene change at the frame level, and simultaneously investigate the local statistical characteristics of scenes such as variance and peak bit rate etc. Based on this analysis, an effective decision function is first constructed for the scene segmentation. Then, we propose a scene-detection algorithm using the defined dynamic threshold model, which can capture the statistical properties of the scene changes. Experimental results using 15 variable bit rate MPEG video traces indicate good performances of the proposed algorithm with significantly improved scene-detection accuracy.     

A gamma fractal noise source model for variable bit rate video servers

In this paper, we model the statistical behavior of real traces of MPEG-4 encoded variable bit rate video data in a digital video server. As performance measures we calculate bounds for the user disk service rate and buffer size. According to our simulations, the Gamma Fractal Noise model for the increment process, which is self-similar, seems to be very close to the actual data behavior.     

Capturing the spatio-temporal behavior of real traffic data

Traffic data, such as disk and memory accesses, typically exhibits burstiness, temporal locality, and spatial locality. However, except for qualitative speculations, it is not even known how to measure the spatio-temporal correlation, let alone how to re-produce it realistically. In this paper, we propose the “entropy plots” to quantify the correlation and develop a new statistical model, the “PQRS” model, to capture the burstiness and correlation of the real spatio-temporal traffic. Moreover, the model requires very few parameters and offers linear scalability. Experiments with multiple real data sets show that our model can mimic real traces very well.     

Performance analysis of priority scheduling mechanisms under heterogeneous network traffic

Priority scheduling principle plays a crucial role in the Differentiated Services (DiffServ) architecture for the provisioning of Quality-of-Service (QoS) of network-based applications. Analytical modelling and performance evaluation of priority queuing systems have received significant attention and research efforts. However, most existing work has primarily focused on the analysis of priority queuing under either Short Range Dependent (SRD) or Long Range Dependent (LRD) traffic only. Recent studies have shown that realistic traffic reveals heterogeneous nature within modern multi-service networks. With the aim of investigating the impact of heterogeneous traffic on the design and performance of network-based systems, this paper proposes a novel analytical model for priority queuing systems subject to heterogeneous LRD self-similar and SRD Poisson traffic. The key contribution of the paper is to extend the application of the generalized Schilder's theorem (originally a large deviation principle for handling Gaussian processes only) to deal with heterogeneous traffic and further develop the analytical upper and lower bounds of the queue length distributions for individual traffic flows. The validity and accuracy of the model demonstrated through extensive comparisons between analytical bounds and simulation results make it a practical and cost-effective evaluation tool for investigating the performance behaviour of priority queuing systems under heterogeneous traffic with various parameter settings.     

SenseVid : A traffic trace based tool for QoE Video transmission assessment dedicated to Wireless Video Sensor Networks

Video applications are being a key component to enhance traditional wireless sensor networks (WSN) applications. As a result, sensor network researchers need adequate and easy to use tools to assess the performances of their proposals. The existing transmission evaluation tools either consider video sequences along with codecs that are unsuitable for WSNs or make use of low cost compression methods for still images without inter-frame coding required for efficient video transmission. In this paper, we present SenseVid, an open source video transmission and evaluation tool that considers WSN specific characteristics. Besides low energy intra-frame compression based on fast pruned discrete cosine transform (DCT), a low complexity inter-frame encoding is provided to allow efficient support of video flows. A configurable fine-grain energy model is provided where both video capture and encoding cost are accounted for on a per frame basis. Video traffic differentiation based on priority levels is also provided. SenseVid adopts the video traffic traces approach, allowing its use in any simulation or real testbed environment. Using SenseVid, the user is able to reconstruct the received video considering lost packets during its transmission as well as estimating the achieved quality of service (QoS) and quality of experience (QoE).     

Passive analysis of TCP anomalies

In this paper, we focus on passive measurements of TCP traffic. We propose a heuristic technique to classify TCP anomalies, i.e., segments that have a sequence number different from the expected one, such as out-of-sequence and duplicate segments. Since TCP is a closed-loop protocol that infers network conditions from packet losses and reacts accordingly, the possibility of carefully distinguishing the causes of anomalies in TCP traffic is very appealing and may be instrumental to understand TCP behavior in real environments. We apply the proposed heuristic to traffic traces collected at both network edges and backbone links. By comparing results obtained from traces collected over several years, we observe some phenomena such as the impact of the introduction of TCP SACK which reduces the unnecessary retransmissions, the large percentage of network reordering, etc. By further studying the statistical properties of TCP anomalies, we find that, while their aggregate exhibits long-range dependence, anomalies suffered by individual long-lived flows are on the contrary uncorrelated. Interestingly, no dependence on the actual link load is observed.     

Interlayer Jitter Index for the Transmission of Layered Video Stream over the Internet

A novel scheme of dynamic bandwidth allocation and buffer dimensioning based on the video playback tunnel and the jitter_index tunnel is proposed to guarantee the synchronization between the basic layer video stream and the enhancement layer video streams in the transmission of layered video streams over the Internet. The performance of the proposed scheme is evaluated using a set of real-life video traces with the focus on the effects of bandwidth, traffic burstiness and network traffic loading on the statistics of jitter_index between the basic layer and enhancement layers. The numerical results show that the proposed dynamic bandwidth allocation and buffer dimensioning scheme is able to significantly reduce the effect of interlayer jitters in the transmission of multiple layer-coded video streams over the Internet.     

Impact of video scheduling on bandwidth allocation for multiplexed MPEG streams

We present efficient schemes for scheduling the delivery of variable-bit-rate MPEG-compressed video with stringent quality-of-service (QoS) requirements. Video scheduling is being used to improve bandwidth allocation at a video server that uses statistical multiplexing to aggregate video streams prior to transporting them over a network. A video stream is modeled using a traffic envelope that provides a deterministic time-varying bound on the bit rate. Because of the periodicity in which frame types in an MPEG stream are typically generated, a simple traffic envelope can be constructed using only five parameters. Using the traffic-envelope model, we show that video sources can be statistically multiplexed with an effective bandwidth that is often less than the source peak rate. Bandwidth gain is achieved without sacrificing the stringency of the requested QoS. The effective bandwidth depends on the arrangement of the multiplexed streams, which is a measure of the lag between the GOP periods of various streams. For homogeneous streams, we give an optimal scheduling scheme for video sources at a video-on-demand server that results in the minimum effective bandwidth. For heterogeneous sources, a sub-optimal scheduling scheme is given, which achieves acceptable bandwidth gain. Numerical examples based on traces of MPEG-coded movies are used to demonstrate the effectiveness of our schemes.