Distributed context-aware visualization

We present a visualization framework integrated in a context-aware system that uses a common underlying stream processing middleware for tight integration of data accessing, processing, and visualization. Context-aware systems are often realized on mobile devices that do not have the computational power to perform complex tasks. Therefore, a dedicated hardware infrastructure might be required for data processing. In our case, stream processing is used, supporting parallelism on distributed and shared memory multiprocessors. We present the integration of visualization modules into a Java-based stream processing framework for context-aware systems, with focus on efficient communication and parallelization. Our approach is demonstrated for the example of a flow visualization scenario.