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neck and a single point of failure. Peer-to-peer
(P2P) approaches, on the other hand, have been
proposed to overcome these obstacles and are
gaining popularity in recent years. P2P systems
such as Gnutella (Gnutella) and Freenet (Freenet)
allow nodes to interconnect freely and have low
maintenance overhead, making it easy to handle
the dynamic changes of peers and their data.
The past years have seen an increased focus on
decentralized P2P systems (Han, et al., 2006,
Li, et al., 2006, Liu, et al., 2004, Morselli, et al.,
2005). However, a query has to be flooded to all
the nodes in a network including the nodes that do
not have relevant data. The fundamental problem
that makes search in these systems difficult is that
data are randomly distributed in the network with
respect to their semantics. Given a search request,
the system either has to search a large number of
nodes or run a risk of missing relevant data. Other
P2P systems such as Chord (Stoica, et al., 2001),
CAN (Ratnasamy, et al., 2001), Pastry (Rowstron,
et al., 2001) and Tapestry (Zhao, et al., 2004) typi-
cally implement distributed hash tables (DHTs)
and use hashed keys to direct a search request to
the specific nodes by leveraging a structured net-
work. In these systems, a data object is associated
with a key which can be produced by hashing the
object name. A node is assigned with an identifier
which shares the same space as the keys. Each
node is responsible for storing a range of keys and
corresponding objects. When a search request is
issued from a node, the search message is routed
through the network to the node responsible for
the key. They can guarantee to complete search
in a logarithmic number of steps. Over years,
many applications have been developed, such as
file sharing (LimeWire) and content distribution
(Castro, et al., 2003).
In this article, we propose a two-tier semantic
P2P network to search for context information in
wide-area networks. The basic idea is to construct a
two-level semantic P2P network based on metadata
(i.e., context ontologies), which is essentially a
semantic approach, to facilitate efficient search.
In this system, context data are represented by
a collection of RDF (RDF) triples. Peers with
the same semantics are grouped together into a
semantic cluster in the upper-tier network. All
the semantic clusters are constructed as a one-
dimensional semantic ring space. This is achieved
by dedicating part of hashed node identifiers to
correspond to their data semantics. Data semantic
is extracted according to a set of schemas. Peers
in each semantic cluster can be organized as a
structured P2P network such as Chord identifier
space in the lower-tier network. Thus, all the
nodes in the same semantic cluster know which
node is responsible for storing context data triples
they are looking for, and context queries can be
efficiently routed to those nodes.
The rest of the article is organized as fol-
lows. Section 2 presents the detail of the two-tier
semantic P2P network. Section 3 evaluates the
performance of our system using simulation and
presents the results. Section 4 reviews related
works, and finally Section 5 concludes our work.
THE TWO-TIER SEMANTIC
P2P NETWORK
In this section, we first present an overview of
the two-tier semantic P2P network, followed
by a description of technical details. For ease
of discussion, we use the terms node and peer
interchangeably for the rest of the article.
OVERVIEW
In this network, a large number of nodes storing
context data are grouped and self-organized into
a two-tier semantic P2P network, in accordance
with their semantics. A node can act as producer,
consumer or both. Producers provide various
context data for sharing whereas consumers obtain
context data by submitting their context queries
and receiving results. Each node maintains a lo-
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