882 research outputs found
Fast Freenet: Improving Freenet Performance by Preferential Partition Routing and File Mesh Propagation
The Freenet Peer-to-Peer network is doing a good job
in providing anonymity to the users. But the performance
of the network in terms of download speed and request hit
ratio is not that good.
We propose two modifications to Freenet in order to improve
the download speed and request hit ratio for all participants.
To improve download speed we propose Preferential
Partition Routing, where nodes are grouped according
to bandwidth and slow nodes are discriminated when routing.
For improvements in request hit ratio we propose File
Mesh propagation where each node sends fuzzy information
about what documents it posesses to its neigbors.
To verify our proposals we simulate the Freenet network
and the bandwidth restrictions present between nodes as
well as using observed distributions for user actions to show
how it affects the network.
Our results show an improvement of the request hit ratio
by over 30 times and an increase of the average download
speed with six times, compared to regular Freenet routing
The essence of P2P: A reference architecture for overlay networks
The success of the P2P idea has created a huge diversity
of approaches, among which overlay networks, for example,
Gnutella, Kazaa, Chord, Pastry, Tapestry, P-Grid, or DKS,
have received specific attention from both developers and
researchers. A wide variety of algorithms, data structures,
and architectures have been proposed. The terminologies
and abstractions used, however, have become quite inconsistent since the P2P paradigm has attracted people from many different communities, e.g., networking, databases, distributed systems, graph theory, complexity theory, biology, etc. In this paper we propose a reference model for overlay networks which is capable of modeling different approaches in this domain in a generic manner. It is intended to allow researchers and users to assess the properties of concrete systems, to establish a common vocabulary for scientific discussion, to facilitate the qualitative comparison of the systems, and to serve as the basis for defining a standardized API to make overlay networks interoperable
NextBestOnce: Achieving Polylog Routing despite Non-greedy Embeddings
Social Overlays suffer from high message delivery delays due to insufficient
routing strategies. Limiting connections to device pairs that are owned by
individuals with a mutual trust relationship in real life, they form topologies
restricted to a subgraph of the social network of their users. While
centralized, highly successful social networking services entail a complete
privacy loss of their users, Social Overlays at higher performance represent an
ideal private and censorship-resistant communication substrate for the same
purpose.
Routing in such restricted topologies is facilitated by embedding the social
graph into a metric space. Decentralized routing algorithms have up to date
mainly been analyzed under the assumption of a perfect lattice structure.
However, currently deployed embedding algorithms for privacy-preserving Social
Overlays cannot achieve a sufficiently accurate embedding and hence
conventional routing algorithms fail. Developing Social Overlays with
acceptable performance hence requires better models and enhanced algorithms,
which guarantee convergence in the presence of local optima with regard to the
distance to the target.
We suggest a model for Social Overlays that includes inaccurate embeddings
and arbitrary degree distributions. We further propose NextBestOnce, a routing
algorithm that can achieve polylog routing length despite local optima. We
provide analytical bounds on the performance of NextBestOnce assuming a
scale-free degree distribution, and furthermore show that its performance can
be improved by more than a constant factor when including Neighbor-of-Neighbor
information in the routing decisions.Comment: 23 pages, 2 figure
Recommended from our members
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
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
Effects of Knowledge Base Quality on Peer-to-peer Information Propagation
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