15 research outputs found
Improving files availability for BitTorrent using a diffusion model
The BitTorrent mechanism effectively spreads file fragments by copying the
rarest fragments first. We propose to apply a mathematical model for the
diffusion of fragments on a P2P in order to take into account both the effects
of peer distances and the changing availability of peers while time goes on.
Moreover, we manage to provide a forecast on the availability of a torrent
thanks to a neural network that models the behaviour of peers on the P2P
system. The combination of the mathematical model and the neural network
provides a solution for choosing file fragments that need to be copied first,
in order to ensure their continuous availability, counteracting possible
disconnections by some peers
ISP-friendly Peer-assisted On-demand Streaming of Long Duration Content in BBC iPlayer
In search of scalable solutions, CDNs are exploring P2P support. However, the
benefits of peer assistance can be limited by various obstacle factors such as
ISP friendliness - requiring peers to be within the same ISP, bitrate
stratification - the need to match peers with others needing similar bitrate,
and partial participation - some peers choosing not to redistribute content.
This work relates potential gains from peer assistance to the average number
of users in a swarm, its capacity, and empirically studies the effects of these
obstacle factors at scale, using a month-long trace of over 2 million users in
London accessing BBC shows online. Results indicate that even when P2P swarms
are localised within ISPs, up to 88% of traffic can be saved. Surprisingly,
bitrate stratification results in 2 large sub-swarms and does not significantly
affect savings. However, partial participation, and the need for a minimum
swarm size do affect gains. We investigate improvements to gain from increasing
content availability through two well-studied techniques: content bundling -
combining multiple items to increase availability, and historical caching of
previously watched items. Bundling proves ineffective as increased server
traffic from larger bundles outweighs benefits of availability, but simple
caching can considerably boost traffic gains from peer assistance.Comment: In Proceedings of IEEE INFOCOM 201
A Cooperation-Driven ICN-based Caching Scheme for Mobile Content chunk Delivery at RAN
In order to resolve the tension between continuously growing mobile users’ demands on content access and the scarcity of the bandwidth capacity over backhaul links, we propose in this paper a fully distributed ICN-based caching scheme for content objects in Radio Access Network (RAN) at eNodeBs. Such caching scheme operates in a cooperative way within neighbourhoods, aiming to reduce cache redundancy so as to improve the diversity of content distribution. The caching decision logic at individual eNodeBs allows for adaptive caching, by taking into account dynamic context information, such as content popularity and availability. The efficiency of the proposed distributed caching scheme is evaluated via extensive simulations, which show great performance gains, in terms of a substantial reduction of backhaul content traffic as well as great improvement on the diversity of content distribution, etc
Estimating Self-Sustainability in Peer-to-Peer Swarming Systems
Peer-to-peer swarming is one of the \emph{de facto} solutions for distributed
content dissemination in today's Internet. By leveraging resources provided by
clients, swarming systems reduce the load on and costs to publishers. However,
there is a limit to how much cost savings can be gained from swarming; for
example, for unpopular content peers will always depend on the publisher in
order to complete their downloads. In this paper, we investigate this
dependence. For this purpose, we propose a new metric, namely \emph{swarm
self-sustainability}. A swarm is referred to as self-sustaining if all its
blocks are collectively held by peers; the self-sustainability of a swarm is
the fraction of time in which the swarm is self-sustaining. We pose the
following question: how does the self-sustainability of a swarm vary as a
function of content popularity, the service capacity of the users, and the size
of the file? We present a model to answer the posed question. We then propose
efficient solution methods to compute self-sustainability. The accuracy of our
estimates is validated against simulation. Finally, we also provide closed-form
expressions for the fraction of time that a given number of blocks is
collectively held by peers.Comment: 27 pages, 5 figure
A New Stable Peer-to-Peer Protocol with Non-persistent Peers
Recent studies have suggested that the stability of peer-to-peer networks may
rely on persistent peers, who dwell on the network after they obtain the entire
file. In the absence of such peers, one piece becomes extremely rare in the
network, which leads to instability. Technological developments, however, are
poised to reduce the incidence of persistent peers, giving rise to a need for a
protocol that guarantees stability with non-persistent peers. We propose a
novel peer-to-peer protocol, the group suppression protocol, to ensure the
stability of peer-to-peer networks under the scenario that all the peers adopt
non-persistent behavior. Using a suitable Lyapunov potential function, the
group suppression protocol is proven to be stable when the file is broken into
two pieces, and detailed experiments demonstrate the stability of the protocol
for arbitrary number of pieces. We define and simulate a decentralized version
of this protocol for practical applications. Straightforward incorporation of
the group suppression protocol into BitTorrent while retaining most of
BitTorrent's core mechanisms is also presented. Subsequent simulations show
that under certain assumptions, BitTorrent with the official protocol cannot
escape from the missing piece syndrome, but BitTorrent with group suppression
does.Comment: There are only a couple of minor changes in this version. Simulation
tool is specified this time. Some repetitive figures are remove