63 research outputs found
Analysis and Comparison of P2P Search Methods
The popularity and bandwidth consumption attributed to current Peer-to-Peer file-sharing applications makes the operation of these distributed systems very important for the Internet community. Efficient object discovery is the first step towards the realization of distributed resource-sharing. In this work, we present a detailed overview of recent and existing search methods for unstructured Peer-to-Peer networks. We analyze the performance of the algorithms relative to various metrics, giving emphasis on the success rate, bandwidth-efficiency and adaptation to dynamic network conditions. Simulation results are used to empirically evaluate the behavior of nine representative schemes under a variety of different environments
SEARCH, REPLICATION AND GROUPING FOR UNSTRUCTURED P2P NETWORKS
In my dissertation, I present a suite of protocols that assist in efficient content location
and distribution in unstructured Peer-to-Peer overlays. The basis of these schemes is
their ability to learn from past interactions, increasing their performance with time.
Peer-to-Peer (P2P) networks are gaining increasing attention from both the scientific
and the large Internet user community. Popular applications utilizing this new technology
offer many attractive features to a growing number of users. P2P systems have
two basic functions: Content search and dissemination. Search (or lookup) protocols define
how participants locate remotely maintained resources. In data dissemination, users
transmit or receive content from single or multiple sites in the network.
P2P applications traditionally operate under purely decentralized and highly dynamic
environments. Unstructured systems represent a particularly interesting class of
P2P networks. Peers form an overlay in an ad-hoc manner, without any guarantees relative
to lookup performance or content availability. Resources are locally maintained,
while participants have limited knowledge, usually confined to their immediate neighborhood
in the overlay.
My work aims at providing effective and bandwidth-efficient searching and data
sharing. A suite of algorithms which provide peers in unstructured P2P overlays with
the state necessary in order to efficiently locate, disseminate and replicate objects is presented.
The Adaptive Probabilistic Search (APS) scheme utilizes directed walkers to
forward queries on a hop-by-hop basis. Peers store success probabilities for each of their
neighbors in order to efficiently route towards object holders. AGNO performs implicit
grouping of peers according to the demand incentive and utilizes state maintained by APS
in order to route messages from content holders towards interested peers, without requiring
any subscription process. Finally, the Adaptive Probabilistic REplication (APRE)
scheme expands on the state that AGNO builds in order to replicate content inside query
intensive areas according to demand
Analysis and Comparison of P2P Search Methods
The popularity and bandwidth consumption attributed to current
Peer-to-Peer file-sharing applications makes the operation of these
distributed systems very important for the Internet community. Efficient
object discovery is the first step towards the realization of distributed
resource-sharing. In this work, we present a detailed overview of recent
and existing search methods for unstructured Peer-to-Peer networks. We
analyze the performance of the algorithms relative to various metrics,
giving emphasis on the success rate, bandwidth-efficiency and adaptation
to dynamic network conditions. Simulation results are used to empirically
evaluate the behavior of nine representative schemes under a variety of
different environments.
(UMIACS-TR-2003-107
APRE: A Replication Method for Unstructured P2P Networks
We present APRE, a replication method for structureless Peer-to-Peer overlays. The goal of our method
is to achieve real-time replication of even the most sparsely located content relative to demand. APRE
adaptively expands or contracts the replica set of an object in order to improve the sharing process and
achieve a low load distribution among the providers. To achieve that, it utilizes search knowledge to identify
possible replication targets inside query-intensive areas of the overlay. We present detailed simulation
results where APRE exhibits both efficiency and robustness relative to the number of requesters and the
respective request rates. The scheme proves particularly useful in the event of flash crowds, managing to
quickly adapt to sudden surges in load
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