A Distributed Publish/Subscribe System for RDF Data - Data Management in Cloud, Grid and P2P Systems - page 39

A Distributed Publish/Subscribe System
for RDF Data
Laurent Pellegrino, Fabrice Huet, Francoise Baude, and Amjad Alshabani
INRIA-I3S-CNRS, University of Nice-Sophia Antipolis
2004 Route des Lucioles, Sophia Antipolis, France
[e-mail]
Abstract. The pub/sub communication style is a prevalent messaging
pattern for filtering information from distributed and large-scale network
(e.g., from the real-time web, sensor networks, etc.) thanks to the decou-
pling between publishers and subscribers. At the same time, persisting
the published information is a prerequisite for any further batch analyt-
ics on such big amount of data. As data can be heterogeneous, reliance
on format from the semantic web such as RDF is unavoidable. In this
paper we introduce two versions of a content-based pub/sub matching
algorithm for RDF described events, working on an adapted version of
the CAN structured P2P network designed to both store and dissemi-
nate RDF events. In contrary to existing pub/sub solutions based upon
structured overlay networks that index semantic events several times due
to the use of hash functions, we leverage the lexicographic order of the
event elements. Thus, only subscriptions and not publications have to be
duplicated, which is better given that in real settings, publications may
occur more frequently than subscriptions. Furthermore, our system al-
lows to publish events made of any number of elements and the subscrip-
tion language leverages the SPARQL query language. The first algorithm
we introduce initially derives from the ideas discussed by Liarou. et al.
based upon rewriting continuous queries along matching RDF elements
(CSBV) with the purpose to perform the matching between subscriptions
and several RDF elements on multiple nodes. The experimental results
discuss the applicability of the presented algorithms to some synthetic
scenarios and identify, accordingly, which pub/sub matching algorithm
isthemorerelevant.
1 Introduction
The advent of the Semantic Web by the precursor Tim Bernes-Lee incites avail-
able information on the World Wide Web to become more and more structured.
Structured contents are possible thanks to powerful data models such as Re-
source Description Model (RDF) that makes knowledges machine-processable
and machine-understandable. Many centralized solutions such as Jena [4], Sesame
[1] or OWLIM [11] have been proposed the last years to store and retrieve RDF
data. However, they all suffer from their inherent design that is not suitable to
scale with the perpetual increase of the resources available on the Web. Some