4,598 research outputs found
Predicting the Impact of Measures Against P2P Networks on the Transient Behaviors
The paper has two objectives. The first is to study rigorously the transient
behavior of some P2P networks whenever information is replicated and
disseminated according to epidemic-like dynamics. The second is to use the
insight gained from the previous analysis in order to predict how efficient are
measures taken against peer-to-peer (P2P) networks. We first introduce a
stochastic model which extends a classical epidemic model and characterize the
P2P swarm behavior in presence of free riding peers. We then study a second
model in which a peer initiates a contact with another peer chosen randomly. In
both cases the network is shown to exhibit a phase transition: a small change
in the parameters causes a large change in the behavior of the network. We
show, in particular, how the phase transition affects measures that content
provider networks may take against P2P networks that distribute non-authorized
music or books, and what is the efficiency of counter-measures.Comment: IEEE Infocom (2011
A stochastic epidemiological model and a deterministic limit for BitTorrent-like peer-to-peer file-sharing networks
In this paper, we propose a stochastic model for a file-sharing peer-to-peer
network which resembles the popular BitTorrent system: large files are split
into chunks and a peer can download or swap from another peer only one chunk at
a time. We prove that the fluid limits of a scaled Markov model of this system
are of the coagulation form, special cases of which are well-known
epidemiological (SIR) models. In addition, Lyapunov stability and settling-time
results are explored. We derive conditions under which the BitTorrent
incentives under consideration result in shorter mean file-acquisition times
for peers compared to client-server (single chunk) systems. Finally, a
diffusion approximation is given and some open questions are discussed.Comment: 25 pages, 6 figure
Efficient data representation for XML in peer-based systems
Purpose - New directions in the provision of end-user computing experiences mean that the best way to share data between small mobile computing devices needs to be determined. Partitioning large structures so that they can be shared efficiently provides a basis for data-intensive applications on such platforms. The partitioned structure can be compressed using dictionary-based approaches and then directly queried without firstly decompressing the whole structure. Design/methodology/approach - The paper describes an architecture for partitioning XML into structural and dictionary elements and the subsequent manipulation of the dictionary elements to make the best use of available space. Findings - The results indicate that considerable savings are available by removing duplicate dictionaries. The paper also identifies the most effective strategy for defining dictionary scope. Research limitations/implications - This evaluation is based on a range of benchmark XML structures and the approach to minimising dictionary size shows benefit in the majority of these. Where structures are small and regular, the benefits of efficient dictionary representation are lost. The authors' future research now focuses on heuristics for further partitioning of structural elements. Practical implications - Mobile applications that need access to large data collections will benefit from the findings of this research. Traditional client/server architectures are not suited to dealing with high volume demands from a multitude of small mobile devices. Peer data sharing provides a more scalable solution and the experiments that the paper describes demonstrate the most effective way of sharing data in this context. Social implications - Many services are available via smartphone devices but users are wary of exploiting the full potential because of the need to conserve battery power. The approach mitigates this challenge and consequently expands the potential for users to benefit from mobile information systems. This will have impact in areas such as advertising, entertainment and education but will depend on the acceptability of file sharing being extended from the desktop to the mobile environment. Originality/value - The original work characterises the most effective way of sharing large data sets between small mobile devices. This will save battery power on devices such as smartphones, thus providing benefits to users of such devices
Conjoining Speeds up Information Diffusion in Overlaying Social-Physical Networks
We study the diffusion of information in an overlaying social-physical
network. Specifically, we consider the following set-up: There is a physical
information network where information spreads amongst people through
conventional communication media (e.g., face-to-face communication, phone
calls), and conjoint to this physical network, there are online social networks
where information spreads via web sites such as Facebook, Twitter, FriendFeed,
YouTube, etc. We quantify the size and the critical threshold of information
epidemics in this conjoint social-physical network by assuming that information
diffuses according to the SIR epidemic model. One interesting finding is that
even if there is no percolation in the individual networks, percolation (i.e.,
information epidemics) can take place in the conjoint social-physical network.
We also show, both analytically and experimentally, that the fraction of
individuals who receive an item of information (started from an arbitrary node)
is significantly larger in the conjoint social-physical network case, as
compared to the case where the networks are disjoint. These findings reveal
that conjoining the physical network with online social networks can have a
dramatic impact on the speed and scale of information diffusion.Comment: 14 pages, 4 figure
Poisson limit of an inhomogeneous nearly critical INAR(1) model
An inhomogeneous first--order integer--valued autoregressive (INAR(1))
process is investigated, where the autoregressive type coefficient slowly
converges to one. It is shown that the process converges weakly to a Poisson or
a compound Poisson distribution.Comment: Latex2e pdfeTex Version 3, 22 pages, submitted to ACTA Sci. Math.
(Szeged
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