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Grid-based semantic integration of heterogeneous data resources: Implementation on a HealthGrid
This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.The semantic integration of geographically distributed and heterogeneous data
resources still remains a key challenge in Grid infrastructures. Today's
mainstream Grid technologies hold the promise to meet this challenge in a
systematic manner, making data applications more scalable and manageable. The
thesis conducts a thorough investigation of the problem, the state of the art, and
the related technologies, and proposes an Architecture for Semantic Integration of
Data Sources (ASIDS) addressing the semantic heterogeneity issue. It defines a
simple mechanism for the interoperability of heterogeneous data sources in order
to extract or discover information regardless of their different semantics. The
constituent technologies of this architecture include Globus Toolkit (GT4) and
OGSA-DAI (Open Grid Service Architecture Data Integration and Access)
alongside other web services technologies such as XML (Extensive Markup
Language). To show this, the ASIDS architecture was implemented and tested in a
realistic setting by building an exemplar application prototype on a HealthGrid
(pilot implementation).
The study followed an empirical research methodology and was informed by
extensive literature surveys and a critical analysis of the relevant technologies and
their synergies. The two literature reviews, together with the analysis of the
technology background, have provided a good overview of the current Grid and
HealthGrid landscape, produced some valuable taxonomies, explored new paths
by integrating technologies, and more importantly illuminated the problem and
guided the research process towards a promising solution. Yet the primary
contribution of this research is an approach that uses contemporary Grid
technologies for integrating heterogeneous data resources that have semantically
different. data fields (attributes). It has been practically demonstrated (using a
prototype HealthGrid) that discovery in semantically integrated distributed data
sources can be feasible by using mainstream Grid technologies, which have been
shown to have some Significant advantages over non-Grid based approaches
A democratic Grid: collaboration, sharing and computing for everyone
This paper presents an integrated vision, architecture, middleware and applications of a public and large scale Grid for everyone: supporting collaboration for groups of people who can interact and share work and share or trade computing resources among them. This public Grid is decentralized and self-adapting to the dynamics of the online world with networks, computers and people who come and go, fail and recover and applications with varying loads and resource needs. Initial evaluation based on the first release of the middleware components and applications shows how our Grid can operate in a dynamic and decentralized environment by a combination of pooling and market mechanisms that adapt supply and demand for
resources, self-managing services and applications that react to environmental
changes and generic data-sharing services for concurrent write-sharing. The potential
for societal impact is enormous as it can open Grid computing and collaboration to
everyone on the Internet.Peer ReviewedPostprint (author’s final draft
Data Management in the APPA System
International audienceCombining Grid and P2P technologies can be exploited to provide high-level data sharing in large-scale distributed environments. However, this combination must deal with two hard problems: the scale of the network and the dynamic behavior of the nodes. In this paper, we present our solution in APPA (Atlas Peer-to-Peer Architecture), a data management system with high-level services for building large-scale distributed applications. We focus on data availability and data discovery which are two main requirements for implementing large-scale Grids. We have validated APPA's services through a combination of experimentation over Grid5000, which is a very large Grid experimental platform, and simulation using SimJava. The results show very good performance in terms of communication cost and response time
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