Predictive Early Object Shedding in Media Processing Workflows

Media-rich ubiquitous distributed media processing workflow systems continuously sense users´ needs, status, and the context, filter and fuse a multitude of real-time media data, and react by adapting the environment to the user. One challenge facing these systems is that they need to process real-time data arriving continuously from the sensors and data rates and qualities may vary dramatically. Thus, reducing the amount of unqualified data objects that need to be processed within the underlying media processing workflows can enhance the performance significantly. In this paper, we first focus on the prediction of the output qualities at the actuator, especially in the presence of fusion operators in the workflow. We then present quality-aware early object elimination schemes to enable informed resource savings in continuous real-time media processing workflow middleware.