Study of the Effect of the Wireless Gateway on Incoming Self-Similar Traffic

It has been well established by now that high-speed wireline traffic exhibits self-similar behavior. Due to the important consequences of traffic self-similarity in network design, several studies have assumed that wireless traffic is also self-similar and looked at its effects on network performance. However, due to factors such as power limitations and the wireless channel, it is not straightforward that wireline traffic will remain self-similar as it enters the wireless network. This paper provides an analytical study of the propagation of traffic characteristics as wireline traffic is passed to the wireless network through a gateway. The analysis takes into account buffering and repacking operations performed at the gateway, and models for wireline traffic and the wireless channel. We consider two server models, an instant transfer model, and an energy-conserving one. We show that in most cases, in response to self-similar wireline traffic the gateway will produce self-similar wireless traffic. However, when the gateway operates under an energy-conserving mode and if it has a large buffer, wireline traffic such as non-real-time variable-bit-rate traffic will result in non-self-similar wireless traffic. We also study the delays of packets passing through a gateway that is fed by self-similar traffic and show that their survival function has an asymptotically power-law tail with index smaller than 2.     

Self-similarity in World Wide Web traffic: evidence and possiblecauses

The notion of self-similarity has been shown to apply to wide-area and local-area network traffic. We show evidence that the subset of network traffic that is due to World Wide Web (WWW) transfers can show characteristics that are consistent with self-similarity, and we present a hypothesized explanation for that self-similarity. Using a set of traces of actual user executions of NCSA Mosaic, we examine the dependence structure of WWW traffic. First, we show evidence that WWW traffic exhibits behavior that is consistent with self-similar traffic models. Then we show that the self-similarity in such traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user “think time”, and the superimposition of many such transfers in a local-area network. To do this, we rely on empirically measured distributions both from client traces and from data independently collected at WWW servers     

Self-similarity through high-variability: statistical analysis ofEthernet LAN traffic at the source level

A number of empirical studies of traffic measurements from a variety of working packet networks have demonstrated that actual network traffic is self-similar or long-range dependent in nature-in sharp contrast to commonly made traffic modeling assumptions. We provide a plausible physical explanation for the occurrence of self-similarity in local-area network (LAN) traffic. Our explanation is based on convergence results for processes that exhibit high variability and is supported by detailed statistical analyzes of real-time traffic measurements from Ethernet LANs at the level of individual sources. This paper is an extended version of Willinger et al. (1995). We develop here the mathematical results concerning the superposition of strictly alternating ON/OFF sources. Our key mathematical result states that the superposition of many ON/OFF sources (also known as packet-trains) with strictly alternating ON- and OFF-periods and whose ON-periods or OFF-periods exhibit the Noah effect produces aggregate network traffic that exhibits the Joseph effect. There is, moreover, a simple relation between the parameters describing the intensities of the Noah effect (high variability) and the Joseph effect (self-similarity). An extensive statistical analysis of high time-resolution Ethernet LAN traffic traces confirms that the data at the level of individual sources or source-destination pairs are consistent with the Noah effect. We also discuss implications of this simple physical explanation for the presence of self-similar traffic patterns in modern high-speed network traffic     

Ad hoc wireless network traffic-self-similarity and forecasting

Lots of works have been carried out to discuss the self-similarity of Ethernet and World Wide Web traffic. In this letter, we study the ad hoc wireless network traffic collected in an ad hoc network (AHN) testbed and show that the ad hoc wireless network traffic is self-similar, which validates that AHN traffic is forecastable because self-similar time-series can be forecasted. We apply a fuzzy logic system to ad hoc wireless network traffic forecasting and simulation results show that it performs much better than does an LMS adaptive filter. All these studies are very important for evaluating network capacity and determining the battery power mode based on the forecasted traffic workload     

基于FBM模型的自相似流量建模仿真

网络流量建模是网络规划与性能评价的重要基础,传统的业务模型大多基于泊松模型和马尔可夫排队模型,只具有短程相关性,随着网络业务的不断研究发现,实际网络业务流在很长的时间范围内都具有长程相关性,即一种自相似性。本文采用RMD算法和Fourier变换法对网络流量的自相似模型-FBM模型进行了建模及仿真研究,生成了所需的自相似流量序列。然后分别采用R/S法和方差时间图法对其进行自相似参数检测。结果验证了仿真算法所产生的序列存在着自相似性,并同时对RMD算法和Fourier变换法的优缺点进行了分析。     

Self-similar traffic and network dynamics

One of the most significant findings of traffic measurement studies over the last decade has been the observed self-similarity in packet network traffic. Subsequent research has focused on the origins of this self-similarity, and the network engineering significance of this phenomenon. This paper reviews what is currently known about network traffic self-similarity and its significance. We then consider a matter of current research, namely, the manner in which network dynamics (specifically, the dynamics of transmission control protocol (TCP), the predominant transport protocol used in today's Internet) can affect the observed self-similarity. To this end, we first discuss some of the pitfalls associated with applying traditional performance evaluation techniques to highly-interacting, large-scale networks such as the Internet. We then present one promising approach based on chaotic maps to capture and model the dynamics of TCP-type feedback control in such networks. Not only can appropriately chosen chaotic map models capture a range of realistic source characteristics, but by coupling these to network state equations, one can study the effects of network dynamics on the observed scaling behavior We consider several aspects of TCP feedback, and illustrate by examples that while TCP-type feedback can modify the self-similar scaling behavior of network traffic, it neither generates it nor eliminates it     

自相似业务模型下的队列分析--大偏差技术

近年来对许多实际运行中的网络（局域网和广域网）的测量与分析证实：真实的网络业务具有统计上的自相似性而且是长相关的。传统的排队理论均假定业务是Poisson或Markovian,因此是短相关的,那里的队列分析方法对自相似业务模型是不适用的。大偏差技术是对自相似业务模型进行队列分析的有效方法。本文应用大偏差技术对以FARIMA为业务模型的队列系统进行了分析,结果证明：队列长度尾分布渐进为Weibullian分布,而且与模型的短相关结构无关。     

自相似业务流建模及其合成性能分析

基于通信网络仿真软件平台OPNET中的RPG模型，本文实现了一个通用的、与协议无关的自相似业务流发生模型，并通过仿真实验和小波分析的方法验证了该模型的正确性和可用性。在此模型的基础上，着重对自相似业务流合成过程的性能和行为特性进行了大量的实验和分析。研究结果表明，自相似业务流的合成过程仍具有自相似性，而且合成流的自相似参数接近于各独立输入业务流中所具有的最大自相似参数。     

无限缓存下自相似网络通信量复用策略

研究了自相似网络通信量的统计复用策略。首先讨论了在采用FIFO(First In First Out)服务策略且缓存趋于无限大时,满足一定溢出概率要求的统计复用带宽要求,然后对这种情况进行了仿真分析。研究表明网络通信量的自相似特性对复用增益有较大的影响,并且自相似性越强、复用通信量数量越大,所取得的复用增益越大,这对于网络设计是很重要的。     

自相似业务量的流量控制研究

由于自相似性是宽带网络中业务量的一个普遍特性,因此在进行宽带网络管理和流量控制时必须考虑它所带来的影响。目前,有关基于自相似业务量的流控机制的研究已经引起了人们广泛地注意。一些研究表明自相似业务量表现出了与传统模型不同的排队特征。本文围绕业务质量保证和流量控制机制,具体研究和分析了业务量的自相似性质对业务量成形、用法参数控制和呼叫接纳控制等流量控制机制的影响,并得到了一些重要结论。     

Queue Analysis and Multiplexing of Heavy-tailed Traffic in Wireless Packet Data Networks

Recent research based on traffic measurements shows that Internet traffic flows have a fractal nature (i.e., self-similarity property), which causes an underestimation of network engineering parameters when using the conventional Poisson model. Preliminary field measurements demonstrate that packet data traffic in wireless communications also exhibits self-similarity. In this paper, we investigate the queuing behavior of self-similar traffic flows for data applications in a packet-switching single-server wireless network. The traffic is generated by an on–off source with heavy-tailed on periods and exponentially distributed off periods. We extend previous analysis of a relation among the asymptotic distribution of loss probability, traffic specifications, and transmission rate for a wireline system to a wireless system, taking into account wireless propagation channel characteristics. We also investigate the multiplexing of heavy-tailed traffic flows with a finite buffer for the downlink transmission of a wireless network. Computer simulation results demonstrate that assumptions made in the theoretical analysis are reasonable and the derived relationships are accurate.     

Models for wireless H.264 video-on-demand services using self-similarity and heavy-tails

In this work two video-on-demand (VoD) capacity models for H.264 video traces transmitted using 802.11g are proposed, one based on a self-similar traffic distribution and the other one based in the summation of a large number of Pareto distributed random variables. To ascertain the validity of using such modeling techniques a statistical analysis was performed where it was found that H.264 video traces exhibit self-similarity and heavy-tailed properties, as previous video formats that also use variable bit rate encoding. The models were evaluated against trace based simulations using ns-3 and results from hardware testbeds from other works. The model based on Pareto distributions gives a lower bound on a wide range of buffer sizes, while the model based on self-similarity provides a closer approximation to the user load when buffer size is high. The results show that the models can approximate the maximum user load for H.264 transmission on a local area VoD system and that they depend on the access point buffer size and the desired quality of service expressed as packet-loss probability.     

On multimedia networks: self-similar traffic and networkperformance

The main objective in telecommunications network engineering is to have as many happy users as possible. In other words, the network engineer has to resolve the trade-off between capacity and QoS requirements. Accurate modeling of the offered traffic load is the first step in optimizing resource allocation algorithms such that provision of services complies with the QoS constraints while maintaining maximum capacity. As broadband multimedia services became popular, they necessitated new traffic models with self-similar characteristics. We present a survey of the self-similarity phenomenon observed in multimedia traffic and its implications on network performance. Our current research aims to fill the gap between this new traffic model and network engineering. An immediate consequence of this study is the demonstration of the limitations or validity of conventional resource allocation methods in the presence of self-similar traffic     

网络业务流的自相似性

对通信网络的大量研究表明,网络业务本质是自相似的(相关函数上表现为长相关特性)。网络业务的统计自相似性主要是指在不同时间尺度上观测到的业务流量序列具有相同的统计特性。讨论了当前网络业务流的特性;分析了现有的自相似业务流模型。为在线测量网络中的高速业务流,根据实测时间序列数据建立合适模型提供了参考。     

自相似业务流复用特性分析

现有研究将复用的自相似业务流Hurst参数值确定为各个业务流中最大的H参数值，与业务流的其他性质无关，这一结论用于网络设备的设计不利于网络资源的有效利用。本文采用简单近似估算，并用分形布朗运动模型生成自相似业务流，彩用小波分析方法估计Hurst参数值。实验结果表明，由于复用合成业务流的渐近自相似的本质，在可以观测的时间尺度范围内业务流的Hurst参数比这理论预测值小；在一定的序列长度下，复用流的Hurst参数的不仅和最大Hurst参数业务流有关，还受到其它业务流，特别是业务流的方差系数所表现出的短时突发性影响，因此对合成业务流的自相似参数具有重要的影响。     

Book reviews: a summary of multifractal traffic modeling

One of the most important discoveries about Internet traffic is the scaling phenomenon. Different from the traditional traffic pattern, primarily the Poisson model, this type of traffic shows a slowly decaying dependence structure and can be approximately characterized by a self-similar process. Multiscale behavior is a more complex version of self-similarity, indicating that the scaling property of the traffic process isn't uniform across multiple time scales and orders of statistics. It's often modeled with the multifractal process. "Multifractal Based Network Traffic Modeling" provides an accessible but somewhat narrow summary of the research on self-similar and multiscale traffic.     

Self-similar processes in communications networks

This paper reviews and discusses the known definitions and properties of second-order self-similar discrete-time processes and supplements them with some more general conditions of self-similarity. A model for ATM cell traffic is presented and self-similarity conditions of this model are found. This study is motivated by observations that traffic in many real communication networks is self-similar in nature     

自相似网络通信量模型研究综述

越来越多的研究表明网络通信量不是Markov过程,而是在任意时间尺度上都具有突发特性,即自相似特性。描述网络通信量的数学模型主要有自相似和长相关结构。网络的某些参数服从重尾分布,从而导致网络通信量时间尺度上的突发特性。该文分析了传统网络通信量模型和性能分析的弊端,描述了新型网络通信量模型应该具有的基本特征。本文重点研究了网络自相似通信量相关的ON/OFF模型、用户访问概率模型和网络流量闭环模型,讨论了相关的研究方向,并总结了在研究网络通信量模型的过程中应该注意的原则和问题。     

Some results on the self-similarity property in communication networks

Due to the strong experimental evidence that packet network traffic is self-similar in nature, it is important to study the problems to see whether the superposition of self-similar processes retains the property of self-similarity, and whether the service of a server changes the self-similarity property of the input traffic. In this letter, we first discuss some definitions and superposition properties of self-similar processes. We obtain some good results about the property of merging self-similar data streams. Then we present a model of a single server with infinite buffer and prove that when the queue length has finite second-order moment, the input process, being strong asymptotically second-order self-similar (sas-s), is equivalent to the output process which also bears the sas-s property.