Inverting sampled ADSL traffic

On the basis of a reference model for ADSL traffic on an IP backbone link, established in an earlier study, we show in this paper that it is possible to infer the characteristics of long flows by performing a deterministic $1/N$ packet sampling. By using the fact that the number of active long flows can be represented by means of the number of customers in an $M/G/\infty$ queue with Weibullian service times, we derive some probabilistic properties of sampled data. These properties are then used to infer the characteristics of original flows. The method is illustrated by considering an actual traffic trace captured in the France Telecom IP backbone network. Experimental data show that the method proves quite efficient

On the Statistical Characterization of Flows in Internet Traffic with Application to Sampling

A new method of estimating some statistical characteristics of TCP flows in the Internet is developed in this paper. For this purpose, a new set of random variables (referred to as observables) is defined. When dealing with sampled traffic, these observables can easily be computed from sampled data. By adopting a convenient mouse/elephant dichotomy also dependent on traffic, it is shown how these variables give a reliable statistical representation of the number of packets transmitted by large flows during successive time intervals with an appropriate duration. A mathematical framework is developed to estimate the accuracy of the method. As an application, it is shown how one can estimate the number of large TCP flows when only sampled traffic is available. The algorithm proposed is tested against experimental data collected from different types of IP networks

Inference of Flow Statistics via Packet Sampling in the Internet

We show in this note that by deterministic packet sampling, the tail of the distribution of the original flow size can be obtained by rescaling that of the sampled flow size. To recover information on the flow size distribution lost through packet sampling, we propose some heuristics based on measurements from different backbone IP networks. These heuristic arguments allow us to recover the complete flow size distribution

On the Statistical Characterization of Flows in Internet Traffic with Application to Sampling

20 pagesA new method of estimating some statistical characteristics of TCP flows in the Internet is developed in this paper. For this purpose, a new set of random variables (referred to as observables) is defined. When dealing with sampled traffic, these observables can easily be computed from sampled data. By adopting a convenient mouse/elephant dichotomy also dependent on traffic, it is shown how these variables give a reliable statistical representation of the number of packets transmitted by large flows during successive time intervals with an appropriate duration. A mathematical framework is developed to estimate the accuracy of the method. As an application, it is shown how one can estimate the number of large TCP flows when only sampled traffic is available. The algorithm proposed is tested against experimental data collected from different types of IP networks

ネットワーク エノ ソウキ テンカイ オ カノウ トスル ケイリョウナ イジョウ トラヒック ブンセキ シュホウ ノ カクリツ ニ カンスル ケンキュウ

博士(工学)大阪市立大

Distributed multimedia systems

A distributed multimedia system (DMS) is an integrated communication, computing, and information system that enables the processing, management, delivery, and presentation of synchronized multimedia information with quality-of-service guarantees. Multimedia information may include discrete media data, such as text, data, and images, and continuous media data, such as video and audio. Such a system enhances human communications by exploiting both visual and aural senses and provides the ultimate flexibility in work and entertainment, allowing one to collaborate with remote participants, view movies on demand, access on-line digital libraries from the desktop, and so forth. In this paper, we present a technical survey of a DMS. We give an overview of distributed multimedia systems, examine the fundamental concept of digital media, identify the applications, and survey the important enabling technologies.published_or_final_versio

Audio quality and capacity issues in network design

Data networks are an integral part of the professional audio environment. The emphasis in audio networking is moving towards the real-time transfer of audio data. This requires the timely and reliable delivery of audio data. This paper examines a number of quality and capacity issues surrounding the transfer of high quality audio data in real-time over data networks. Areas such as noise, jitter and other types of errors are examined in relation to audio transfer. The paper also includes an overview of the hearing process, compression schemes and a review of perceptual encoding techniques. Important network tools such as Quality of Service and Error Correction are also examined in the context of transferring audio data

Operational support systems for satellite communications

The role of satellite communications is changing from providing bandwidth linking network operators interconnections towards providing IP enabled communications to end users. This migration from few high-value routes towards many low-value routes means that integration and automation of processes with terrestrial networks becomes critical in driving down unit costs. Integration and automation is necessary on all planes: user, control and management. In satellite communications, management aspects, underpinned by Operational Support Systems (OSS) have received the least research attention, making this a valuable topic for study. In most areas, OSS for satellite systems are similar to other domains. However there are some notable areas of difference which have been the focus of this research. The eTOM business framework, developed by the TMF, has been used to highlight aspects of OSS unique to satellite. Since satellite capacity represents the highest operational cost of a satellite route, effective management while minimising the overhead traffic is critical. The transmission of IP packets is assumed and the real-time measurement of QoS parameters such as packet delay and loss emerged as the most important differences. A number of approaches to QoS measurement are feasible, however the use of trace packets is most promising especially for high network loads. An experiment compares the results from simulations, mathematical models and from a test network, using Poisson and self-similar traffic flows. The relationship between measurement accuracy and trace packet intensity is explored and the measurement response time to steps in traffic load is estimated. It is discovered that measurement accuracy improves as the queue load increases, in contrast to alternative approaches such as sampling of user packets. The response time to steps depends upon the degree of self-similarity and is generally longer than the times recommended by standards. A pragmatic approach to management of different modes is proposed where the measurement method is changed depending on the load

Efficient algorithms for passive network measurement

Network monitoring has become a necessity to aid in the management and operation of large networks. Passive network monitoring consists of extracting metrics (or any information of interest) by analyzing the traffic that traverses one or more network links. Extracting information from a high-speed network link is challenging, given the great data volumes and short packet inter-arrival times. These difficulties can be alleviated by using extremely efficient algorithms or by sampling the incoming traffic. This work improves the state of the art in both these approaches. For one-way packet delay measurement, we propose a series of improvements over a recently appeared technique called Lossy Difference Aggregator. A main limitation of this technique is that it does not provide per-flow measurements. We propose a data structure called Lossy Difference Sketch that is capable of providing such per-flow delay measurements, and, unlike recent related works, does not rely on any model of packet delays. In the problem of collecting measurements under the sliding window model, we focus on the estimation of the number of active flows and in traffic filtering. Using a common approach, we propose one algorithm for each problem that obtains great accuracy with significant resource savings. In the traffic sampling area, the selection of the sampling rate is a crucial aspect. The most sensible approach involves dynamically adjusting sampling rates according to network traffic conditions, which is known as adaptive sampling. We propose an algorithm called Cuckoo Sampling that can operate with a fixed memory budget and perform adaptive flow-wise packet sampling. It is based on a very simple data structure and is computationally extremely lightweight. The techniques presented in this work are thoroughly evaluated through a combination of theoretical and experimental analysis.Postprint (published version