A multi-agent system for parallelizing image analysis tasks

To exploit the full capacity of distributed systems for image analysis tasks they must be processed in parallel. However, developing parallel programs is complicated and often results in architecture-dependent code that is difficult to port to different machines. Thus there is the need of more flexible, architecture independent methods for an automatic parallelization of tasks. This paper introduces such a method and describes a multi-agent system for the automatic parallelization of image analysis tasks. The user provides a specification of the task that is used by the agents to plan and control its parallel processing within a distributed system. At this, they make use of different methods of parallel processing and consider the specific qualification and the actual load of processors when deciding about the scheduling and mapping of tasks and data.