Abstract-Band - Fakultät für Informatik, TU Wien - Technische ...
Abstract-Band - Fakultät für Informatik, TU Wien - Technische ...
Abstract-Band - Fakultät für Informatik, TU Wien - Technische ...
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Sanjin Sehic<br />
COPAL: An Adaptive Approach to Context Provisioning<br />
Studium: Masterstudium Software Engineering & Internet Computing<br />
Betreuer: Univ.Prof. Dr. Schahram Dustdar<br />
Context-awareness is one of the cornerstones of mobile and ubiquitous<br />
computing. It refers to the idea that an application can understand its context<br />
to reason about its current situation and perform suitable operations based<br />
on this knowledge. Moreover, as the situation changes over time, the<br />
application should adapt its behavior according to new circumstances, which<br />
would increase its usability and effectiveness. This thesis introduces the<br />
COPAL (COntext Provisioning for ALl) middleware an adaptive approach to<br />
context provisioning. The COPAL middleware is a flexible and scalable<br />
context-aware service platform that provides a new publish-process-listen<br />
programming model. Its loosely-coupled and modular implementation allows<br />
the system to be customized for different use-cases and deployed on<br />
different platforms. The COPAL programming model separates the task of<br />
context-awareness into three independent steps supported by three looselycoupled<br />
components: publishers, processors, and listeners. This component<br />
design enables developers to progressively extend the system to support new<br />
types of context information and various context-aware applications.<br />
Furthermore, the thesis presents a customizable processing mechanism that<br />
dynamically couples context information with its processing. This mechanism<br />
is the key concepts in the COPAL middleware by which a wide range of<br />
operations can be carried out. Most importantly, it can be used to infer new<br />
context information and to provide some context information at different<br />
levels of granularity.<br />
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