Using semantic mappings for semantic based publish/subscribe systems
Citation:
Song Guo, 'Using semantic mappings for semantic based publish/subscribe systems', [thesis], Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2009, pp 159Download Item:
Guo, Song_TCD-SCSS-PHD-2009-03.pdf (PDF) 12.13Mb
Abstract:
Routing of information within heterogeneous, distributed network domains (e.g. communication
networks, ubiquitous computing environments) is a key challenge that must be tackled for such
environments to be successful. Increasingly, it is accepted that such routing systems need to
cope with mobile and volatile sources and destinations of heterogeneous information, and
Semantic-based Publish/Subscribe (SBPS) systems have been proposed as a means to support
this. However such systems typically assume a common semantic model underpinning the
routing.
Devices, network resources and applications within network domain environments are likely to
be heterogeneous, as they will be produced by different vendors who will each have different
priorities and design philosophies. It is unlikely that a single standardized semantic model for
communication will gain widespread adoption and the need for exchange of heterogeneous
information will persist. The SBPS systems must allow applications/SBPS routers to use
different semantic models to communicate with each other without the necessity of custom
building gateways. Finally the system must support flexible, adaptive semantic interoperability
to cater for the dynamics of such environments.
The KBNMap system proposed in this thesis uses an adaptive, multi-strategy mapping service
approach (comprising a set of mapping strategies and adaptive strategy selection mechanism)
for the purpose of supporting multiple semantic models within a SBPS, in support of routing
heterogeneous information over a network in an appropriate and adaptive manner. The mapping
strategies are used for efficiently loading semantic mappings for use with distributed and
heterogeneous knowledge-based applications. The probabilistic-based strategy selection
mechanism enables the system to dynamically select the appropriate mapping strategy, in order
to adapt to the dynamics of the environment where aspects of the semantic models, applications
and network environment are constantly changing.
This research advances the state of the art by introducing and evaluating a multi-strategy
mapping approach and adaptive mapping selection mechanism within a SBPS system, including
identification of the key factors that will influence strategy selection.
Author: Guo, Song
Advisor:
O'Sullivan, DeclanQualification name:
Doctor of Philosophy (Ph.D.)Publisher:
Trinity College (Dublin, Ireland). School of Computer Science & StatisticsNote:
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