Cross-Layer Peer-to-Peer Track Identification and Optimization Based on Active Networking

P2P applications appear to emerge as ultimate killer applications due to their ability to construct highly dynamic overlay topologies with rapidly-varying and unpredictable traffic dynamics, which can constitute a serious challenge even for significantly over-provisioned IP networks. As a result, ISPs are facing new, severe network management problems that are not guaranteed to be addressed by statically deployed network engineering mechanisms. As a first step to a more complete solution to these problems, this paper proposes a P2P measurement, identification and optimisation architecture, designed to cope with the dynamicity and unpredictability of existing, well-known and future, unknown P2P systems. The purpose of this architecture is to provide to the ISPs an effective and scalable approach to control and optimise the traffic produced by P2P applications in their networks. This can be achieved through a combination of different application and network-level programmable techniques, leading to a crosslayer identification and optimisation process. These techniques can be applied using Active Networking platforms, which are able to quickly and easily deploy architectural components on demand. This flexibility of the optimisation architecture is essential to address the rapid development of new P2P protocols and the variation of known protocols

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

CLOSER: A Collaborative Locality-aware Overlay SERvice

Current Peer-to-Peer (P2P) file sharing systems make use of a considerable percentage of Internet Service Providers (ISPs) bandwidth. This paper presents the Collaborative Locality-aware Overlay SERvice (CLOSER), an architecture that aims at lessening the usage of expensive international links by exploiting traffic locality (i.e., a resource is downloaded from the inside of the ISP whenever possible). The paper proves the effectiveness of CLOSER by analysis and simulation, also comparing this architecture with existing solutions for traffic locality in P2P systems. While savings on international links can be attractive for ISPs, it is necessary to offer some features that can be of interest for users to favor a wide adoption of the application. For this reason, CLOSER also introduces a privacy module that may arouse the users' interest and encourage them to switch to the new architectur

Peer-to-peer:is deviant behavior the norm on P2P file-sharing networks?

P2P file-sharing networks such as Kazaa, eDonkey, and Limewire boast millions of users. Because of scalability concerns and legal issues, such networks are moving away from the semicentralized approach that Napster typifies toward more scalable and anonymous decentralized P2P architectures. Because they lack any central authority, these networks provide a new, interesting context for the expression of human social behavior. However, the activities of P2P community members are sometimes at odds with what real-world authorities consider acceptable. One example is the use of P2P networks to distribute illegal pornography. To gauge the form and extent of P2P-based sharing of illegal pornography, we analyzed pornography-related resource-discovery traffic in the Gnutella P2P network. We found that a small yet significant proportion of Gnutella activity relates to illegal pornography: for example, 1.6 percent of searches and 2.4 percent of responses are for this type of material. But does this imply that such activity is widespread in the file-sharing population? On the contrary, our results show that a small yet particularly active subcommunity of users searches for and distributes illegal pornography, but it isn't a behavioral norm

Competing against online sharing

Purpose – This paper aims to explore online sharing of copyrighted content over peer‐to‐peer (p2p) file sharing networks and its impact on the music industry, and to assess the viable business models for the industry in the future. Design/methodology/approach – The authors analyze the evolution of the online content market over the years that followed the widespread adoption of p2p. The paper is based on a teaching case, and builds on two related academic papers that provide the theoretical underpinnings for the analysis. Findings – Based on the early developments observed in this marketplace and the aforementioned theoretical work, the paper argues that it is unfeasible to fully eradicate p2p, and so the industry must embrace it by understanding how consumers derive value from the technologies that enable it. Originality/value – The developments analyzed here offer relevant insights for the online content marketplace, allow the scope of strategies available to the music industry to be understood better, and may provide lessons for other industries transitioning to online business models

On the Impact of Practical P2P Incentive Mechanisms on User Behavior

In this paper we report on the results of a large-scale measurement study of two popular peer-topeer systems, namely BitTorrent and eMule, that use practical and lightweight incentive mechanisms to encourage cooperation between users. We focus on identifying the strategic behavior of users in response to those incentive mechanisms. Our results illustrate a gap between what system designers and researchers expect from users in reaction to an incentive mechanism, and how users react to those incentives. In particular, we observe that the majority of BitTorrent users appear to cooperate well, despite the existence of known ways to tamper with the incentive mechanism, users engaging in behavior that could be regarded as cheating comprised only around 10% of BitTorrent’s population. That is, although we know that users can easily cheat, they actually do not currently appear to cheat at a large enough scale. In the eMule system, we identify several distinct classes of users based on their behavior. A large fraction of users appears to perceive cooperation as a good strategy, and openly share all the files they obtained. Other users engage in more subtle strategic choices, by actively optimizing the number and types of files they share in order to improve their standing in eMule’s waiting queues; they tend to remove files for which downloading is complete and keep a limited total volume of files shared

Statistical analysis of a P2P query graph based on degrees and their time-evolution

Despite their crucial impact on the performances of peer-to-peer systems, very few is known on peers behaviors in such networks. We propose here a study of these of these behaviors in a running environment using a semi-centralised p2p system (edonkey). To achieve this, we use a trace of the queries made to a large server managing up to fifty thousands peers simultaneously, and a few thousands query per second. We analyse these data using complex network methods, and focus in particular on the degrees, their correlations, and their time-evolution. Results show a large variety of observed phenomena, including the variety of peers behaviors and heterogeneity of data queries, which should be taken into account when designing p2p systems

Evidence Collection for Forensic Investigation in Peer to Peer Systems

Abstract Peer to Peer(P2P) file sharing networks are amongst the best free sources of information on the internet. Voluntary participation and lack of control makes them a very attractive option to share data anonymously. However a small group of people take advantage of the freedom provided by these networks and share content that is prohibited by law. Apart from copyrighted content, there are cases where people share les related to Child Pornography which is a criminal offense. Law enforcement attempts to track down these offenders by obtaining a court order for search and seizure of computers at a suspect location. These seized computers are forensically examined using storage and memory-forensics tools. However before the search warrant is issued strong evidence must be presented to provide a reason for suspiscion. Deficient investigation in the intial stages might lead to mis-identification of the source and steer the investigation in a wrong direction. Initial evidence collection on peer to peer le sharing networks is a challenge due to the lack of a central point of control and highly dynamic nature of the networks. The goal of this work is to create a working prototype of an initial evidence collection tool for forensics in P2P networks. The prototype is based on the idea that P2P networks could be monitored by introducing modified peer nodes onto the network for a certain time period and recording relevant information about nodes that possess criminally offensive content. Logging information sent by a suspicious node along with timestamps and unique identication information would provide a strong, verfiiable initial evidence. This work presents one such working prototype in alignment with the goals stated above