Analysis of OD Flows (Raw Data)

In a recent paper, Structural Analysis of Network Traffic Flows, we analyzed the set of Origin Destination traffic flows from the Sprint-Europe and Abilene backbone networks. This report presents the complete set of results from analyzing data from both networks. The results in this report are specific to the Sprint-1 and Abilene datasets studied in the above paper. The following results are presented here: 1 Rows of Principal Matrix (V) 2 1.1 Sprint-1 Dataset ................................ 2 1.2 Abilene Dataset.................................. 9 2 Set of Eigenflows 14 2.1 Sprint-1 Dataset.................................. 14 2.2 Abilene Dataset................................... 21 3 Classifying Eigenflows 26 3.1 Sprint-1 Dataset.................................. 26 3.2 Abilene Datase.................................... 44Centre National de la Recherche Scientifique (CNRS) France; Sprint Labs; Office of Naval Research (N000140310043); National Science Foundation (ANI-9986397, CCR-0325701

A flow-based model for Internet backbone traffic

We model traffic on an uncongested backbone link of an IP network using Poisson Shot-noise process and M/G/$\infty$ queue. We validate the model by simulation. We analyze the model accuracy with real traffic traces collected on the Sprint IP backbone network. We show that despite its simplicity, our model provides a good approximation of the real traffic observed on OC-3 links. This model is also very easy to use and requires few simple parameters to be input

Impact of Out-of-Sequence Processing on the Performance of Data Transmission

Application Level Framing (ALF) was proposed by Clark and Tennenhouse as an important concept for developing high performance applications. ALF relies in part on the ability of applications and protocols to process packets independently one from the other. Thus, performance gains one might expect from the use of ALF are clearly related to performance gains one might expect from applications that can handle and process packets received out-of-sequence, as compared to applicatiojn that require in-order delivery (FTP, TELNET, etc.). In this paper, we examine how the ability to process out-of-sequence packets impacts the efficiency of data transmission. We consider both the impact of application parameters such as the time to process a packet by the application, as well as transmission parameters such as transmission delay, loss rate and flow and congestion control characteristics. The performance measure of interest are total latency, buffer requirements, and jitter. We show, using experimental and simulation results, that out-of-sequence processing is beneficial only for very limited ranges of transmission delays and application processing time. We discuss the impact of this on the architecture of communication systems dedicated to distributed multimedia applications

Impact of Network Delay Variation on Multicast Session Performance With TCP-like Congestion Control

Projet MCRWe study the impact of random noise (queueing delay) on the performance of a multicast session. With a simple analytical model, we analyze the throughput degradation within a multicast (one-to-many) tree under TCP-like congestion and flow control. We use the (max,plus) formalism together with methods based on stochastic comparison (association and convex ordering) and on the theory of extremes (Lai and Robbins' notion of maximal characterist- ics) to prove various properties of the throughput. We first prove that the throughput obtained from Golestani's deterministic model [1] is systematic- ally optimistic. In presence of light tailed random noise, we show that the throughput decreases like the inverse of the logarithm of the number of receivers. We find an analytical upper and a lower bound for the throughput degradation. Within these bounds, we characterize the degradation which is obtained for various tree topologies. In particular, we observe that a class of trees commonly found in IP multicast sessions [9] (which we call umbrella trees) is significantly more sensitive to network noise than other topologies

A flow-based model for TCP traffic in an IP backbone network

We present a model of TCP flows suited to Internet backbone traffic, where links are usually not congested. We characterize the traffic using information on flows, i.e., arrival time, size, and duration. The major contribution of this paper is a model capturing the variation of the transmission rate during a TCP flow solely based on the above flow parameters. This model accounts for the dynamics of TCP congestion window and for the Timeout mechanism. It is independent of the packet loss rate and the round-trip time of the connection. We then model the traffic on a backbone link by aggregating TCP flows. Our model is easy to compute, and we show via simulatio- ns that it gives a good approximation of Internet backbone traffic

Exploiting crowd sourced reviews to explain movie recommendation

International audienceStreaming services such as Netflix, M-Go, and Hulu use advanced recommender systems to help their customers identify relevant content quickly and easily. These recommenders display the list of recommended movies organized in sublists labeled with the genre or some more specific labels. Unfortunately , existing methods to extract these labeled sublists require human annotators to manually label movies, which is time-consuming and biased by the views of annotators. In this paper, we design a method that relies on crowd sourced reviews to automatically identify groups of similar movies and label these groups. Our method takes the content of movie reviews available online as input for an algorithm based on Latent Dirichlet Allocation (LDA) that identifies groups of similar movies. We separate the set of similar movies that share the same combination of genre in sublists and personalize the movies to show in each sublist using matrix factorization. The results of a side-by-side comparison of our method against Technicolor's M-Go VoD service are encouraging

A Framework for Reliable Multicast in the Internet

This document presents the {\em Reliable Multicast Framing Protocol} (RMFP). RMFP is an ALF-based framework for protocols that can be integrated as {\em protocol profiles}. In this report two profiles are described: One for {\em Scalable Reliable Multicast} (SRM) and one for the {\em Local Group Concept} (LGC). Additionally to the specifications of RMFP and the profiles the report describes the design and implementation of an object-oriented RMFP link library. The implementation contains an API and a SRM (Scalable Reliable Multicast) profile. Other profiles are planned to follow. The key features of this implementation are the unified API to all protocol profiles implemented and a class interface to include implementations of new protocol profiles in an easy manner