Monitoring Challenges and Approaches for P2P File-Sharing Systems

Since the release of Napster in 1999, P2P file-sharing has enjoyed a dramatic rise in popularity. A 2000 study by Plonka on the University of Wisconsin campus network found that file-sharing accounted for a comparable volume of traffic to HTTP, while a 2002 study by Saroiu et al. on the University of Washington campus network found that file-sharing accounted for more than treble the volume of Web traffic observed, thus affirming the significance of P2P in the context of Internet traffic. Empirical studies of P2P traffic are essential for supporting the design of next-generation P2P systems, informing the provisioning of network infrastructure and underpinning the policing of P2P systems. The latter is of particular significance as P2P file-sharing systems have been implicated in supporting criminal behaviour including copyright infringement and the distribution of illegal pornograph

When is a bottleneck a bottleneck?

Bottlenecks, i.e. local reductions of capacity, are one of the most relevant scenarios of traffic systems. The asymmetric simple exclusion process (ASEP) with a defect is a minimal model for such a bottleneck scenario. One crucial question is "What is the critical strength of the defect that is required to create global effects, i.e. traffic jams localized at the defect position". Intuitively one would expect that already an arbitrarily small bottleneck strength leads to global effects in the system, e.g. a reduction of the maximal current. Therefore it came as a surprise when, based on computer simulations, it was claimed that the reaction of the system depends in non-continuous way on the defect strength and weak defects do not have a global influence on the system. Here we reconcile intuition and simulations by showing that indeed the critical defect strength is zero. We discuss the implications for the analysis of empirical and numerical data.Comment: 8 pages, to appear in the proceedings of Traffic and Granular Flow '1

From the Information Bottleneck to the Privacy Funnel

We focus on the privacy-utility trade-off encountered by users who wish to disclose some information to an analyst, that is correlated with their private data, in the hope of receiving some utility. We rely on a general privacy statistical inference framework, under which data is transformed before it is disclosed, according to a probabilistic privacy mapping. We show that when the log-loss is introduced in this framework in both the privacy metric and the distortion metric, the privacy leakage and the utility constraint can be reduced to the mutual information between private data and disclosed data, and between non-private data and disclosed data respectively. We justify the relevance and generality of the privacy metric under the log-loss by proving that the inference threat under any bounded cost function can be upper-bounded by an explicit function of the mutual information between private data and disclosed data. We then show that the privacy-utility tradeoff under the log-loss can be cast as the non-convex Privacy Funnel optimization, and we leverage its connection to the Information Bottleneck, to provide a greedy algorithm that is locally optimal. We evaluate its performance on the US census dataset

SatERN: a PEP-less solution for satellite communications

In networks with very large delay like satellite IPbased networks, standard TCP is unable to correctly grab the available resources. To overcome this problem, Performance Enhancing Proxies (PEPs), which break the end-to-end connection and simulate a receiver close enough to the sender, can be placed before the links with large delay. Although splitting PEPs does not modify the transport protocol at the end nodes, they prevent the use of security protocols such as IPsec. In this paper, we propose solutions to replace the use of PEPs named SatERN. This proposal, based on Explicit Rate Notification (ERN) protocols over IP, does not split connections and is compliant with IP-in-IP tunneling solutions. Finally, we show that the SatERN solution achieves high satellite link utilization and fairness of the satellite traffic

Predictability and hierarchy in Drosophila behavior

Even the simplest of animals exhibit behavioral sequences with complex temporal dynamics. Prominent amongst the proposed organizing principles for these dynamics has been the idea of a hierarchy, wherein the movements an animal makes can be understood as a set of nested sub-clusters. Although this type of organization holds potential advantages in terms of motion control and neural circuitry, measurements demonstrating this for an animal's entire behavioral repertoire have been limited in scope and temporal complexity. Here, we use a recently developed unsupervised technique to discover and track the occurrence of all stereotyped behaviors performed by fruit flies moving in a shallow arena. Calculating the optimally predictive representation of the fly's future behaviors, we show that fly behavior exhibits multiple time scales and is organized into a hierarchical structure that is indicative of its underlying behavioral programs and its changing internal states

Dynamic and Static congestion models: A review

We begin by providing an overview of the conventional static equilibrium approach. In such model both the flow of trips and congestion delay are assumed to be constant. A drawback of the static model is that the time interval during which travel occurs is not specified so that the model cannot describe changes in the duration of congestion that result from changes in demand or capacity. This limitation is overcome in the Vickrey/Arnott, de Palma Lindsey bottleneck model, which combines congestion in the form of queuing behind a bottleneck with users' trip-timing preferences and departure time decisions. We derive the user equilibrium and social optimum for the basic bottleneck model, and explain how the optimum can be decentralized using a time-varying toll. They then review some extensions of the basic model that encompass elastic demand, user heterogeneity, stochastic demand and capacity and small networks. We conclude by identifying some unresolved modelling issues that apply not only to the bottleneck model but to trip-timing preferences and congestion dynamics in general