4,782 research outputs found
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
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
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Self-organizing peer-to-peer social networks
This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 The Authors.Peer-to-peer (P2P) systems provide a new solution to distributed information and resource sharing because of its outstanding properties in decentralization, dynamics, flexibility, autonomy, and cooperation, summarized as DDFAC in this paper. After a detailed analysis of the current P2P literature, this paper suggests to better exploit peer social relationships and peer autonomy to achieve efficient P2P structure design. Accordingly, this paper proposes Self-organizing peer-to-peer social networks (SoPPSoNs) to self-organize distributed peers in a decentralized way, in which neuron-like agents following extended Hebbian rules found in the brain activity represent peers to discover useful peer connections. The self-organized networks capture social associations of peers in resource sharing, and hence are called P2P social networks. SoPPSoNs have improved search speed and success rate as peer social networks are correctly formed. This has been verified through tests on real data collected from the Gnutella system. Analysis on the Gnutella data has verified that social associations of peers in reality are directed, asymmetric and weighted, validating the design of SoPPSoN. The tests presented in this paper have also evaluated the scalability of SoPPSoN, its performance under varied initial network connectivity and the effects of different learning rules.National Natural Science of Foundation of Chin
Analysis of searching mechanisms in hierarchical p2p based overlay networks
Proceedings of: The 6th Annual Mediterranean Ad Hoc Networking Workshop (Med Hoc Net 2007. (Corfu, Greece), June 2007This work presents a study of searching mechanisms in Peer-to-Peer (p2p) networks. The aim of this research line is to analyse cross-searching mechanisms that will allow the hierarchical interconnection of p2p networks. A set of relevant metrics for interconnection scenarios are defined to evaluate scalability, robustness and routing latency.This work has been partially supported by the European Union under the IST Content (FP6-2006-IST-507295) project and by the Madrid regional government under the Biogridnet (CAM, S-0505/TIC-0101) project.Publicad
Search in Power-Law Networks
Many communication and social networks have power-law link distributions,
containing a few nodes which have a very high degree and many with low degree.
The high connectivity nodes play the important role of hubs in communication
and networking, a fact which can be exploited when designing efficient search
algorithms. We introduce a number of local search strategies which utilize high
degree nodes in power-law graphs and which have costs which scale sub-linearly
with the size of the graph. We also demonstrate the utility of these strategies
on the Gnutella peer-to-peer network.Comment: 17 pages, 14 figure
Error and Attack Tolerance of Layered Complex Networks
Many complex systems may be described not by one, but by a number of complex
networks mapped one on the other in a multilayer structure. The interactions
and dependencies between these layers cause that what is true for a distinct
single layer does not necessarily reflect well the state of the entire system.
In this paper we study the robustness of three real-life examples of two-layer
complex systems that come from the fields of communication (the Internet),
transportation (the European railway system) and biology (the human brain). In
order to cover the whole range of features specific to these systems, we focus
on two extreme policies of system's response to failures, no rerouting and full
rerouting. Our main finding is that multilayer systems are much more vulnerable
to errors and intentional attacks than they seem to be from a single layer
perspective.Comment: 5 pages, 3 figure
Structure of Peer-to-Peer Social Networks
This paper presents a statistical analysis of the structure of Peer-to-Peer
(P2P) social networks that captures social associations of distributed peers in
resource sharing. Peer social networks appear to be mainly composed of pure
resource providers that guarantee high resource availability and reliability of
P2P systems. The major peers that both provide and request resources are only a
small fraction. The connectivity between peers, including undirected, directed
(out and in) and weighted connections, is scale-free and the social networks of
all peers and major peers are small world networks. The analysis also confirms
that peer social networks show in general disassortative correlations, except
that active providers are connected between each other and by active
requesters. The study presented in this paper gives a better understanding of
peer relationships in resource sharing, which may help a better design of
future P2P networks and open the path to the study of transport processes on
top of real P2P topologies.Comment: APS Style, 8 pages, 5 figures and 4 tables. Final versio
Local Search in Unstructured Networks
We review a number of message-passing algorithms that can be used to search
through power-law networks. Most of these algorithms are meant to be
improvements for peer-to-peer file sharing systems, and some may also shed some
light on how unstructured social networks with certain topologies might
function relatively efficiently with local information. Like the networks that
they are designed for, these algorithms are completely decentralized, and they
exploit the power-law link distribution in the node degree. We demonstrate that
some of these search algorithms can work well on real Gnutella networks, scale
sub-linearly with the number of nodes, and may help reduce the network search
traffic that tends to cripple such networks.Comment: v2 includes minor revisions: corrections to Fig. 8's caption and
references. 23 pages, 10 figures, a review of local search strategies in
unstructured networks, a contribution to `Handbook of Graphs and Networks:
From the Genome to the Internet', eds. S. Bornholdt and H.G. Schuster
(Wiley-VCH, Berlin, 2002), to be publishe
Relating Topological Determinants of Complex Networks to Their Spectral Properties: Structural and Dynamical Effects
The largest eigenvalue of a network's adjacency matrix and its associated
principal eigenvector are key elements for determining the topological
structure and the properties of dynamical processes mediated by it. We present
a physically grounded expression relating the value of the largest eigenvalue
of a given network to the largest eigenvalue of two network subgraphs,
considered as isolated: The hub with its immediate neighbors and the densely
connected set of nodes with maximum -core index. We validate this formula
showing that it predicts with good accuracy the largest eigenvalue of a large
set of synthetic and real-world topologies. We also present evidence of the
consequences of these findings for broad classes of dynamics taking place on
the networks. As a byproduct, we reveal that the spectral properties of
heterogeneous networks built according to the linear preferential attachment
model are qualitatively different from those of their static counterparts.Comment: 18 pages, 13 figure
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