1,158 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 Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
Modeling and Control of Rare Segments in BitTorrent with Epidemic Dynamics
Despite its existing incentives for leecher cooperation, BitTorrent file
sharing fundamentally relies on the presence of seeder peers. Seeder peers
essentially operate outside the BitTorrent incentives, with two caveats: slow
downlinks lead to increased numbers of "temporary" seeders (who left their
console, but will terminate their seeder role when they return), and the
copyright liability boon that file segmentation offers for permanent seeders.
Using a simple epidemic model for a two-segment BitTorrent swarm, we focus on
the BitTorrent rule to disseminate the (locally) rarest segments first. With
our model, we show that the rarest-segment first rule minimizes transition time
to seeder (complete file acquisition) and equalizes the segment populations in
steady-state. We discuss how alternative dissemination rules may {\em
beneficially increase} file acquisition times causing leechers to remain in the
system longer (particularly as temporary seeders). The result is that leechers
are further enticed to cooperate. This eliminates the threat of extinction of
rare segments which is prevented by the needed presence of permanent seeders.
Our model allows us to study the corresponding trade-offs between performance
improvement, load on permanent seeders, and content availability, which we
leave for future work. Finally, interpreting the two-segment model as one
involving a rare segment and a "lumped" segment representing the rest, we study
a model that jointly considers control of rare segments and different uplinks
causing "choking," where high-uplink peers will not engage in certain
transactions with low-uplink peers.Comment: 18 pages, 6 figures, A shorter version of this paper that did not
include the N-segment lumped model was presented in May 2011 at IEEE ICC,
Kyot
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