Resource Prediction And Quality Control For Parallel Execution Of Heterogeneous Medical Imaging Tasks

We have established a novel control system for combining the parallel execution of deterministic and non-deterministic medical imaging applications on a single platform, sharing the same constrained resources. The control system aims at avoiding resource overload and ensuring throughput and latency of critical applications, by means of accurate resourceusage prediction. Our approach is based on modeling the required computation tasks, by employing a combination of weighted moving-average filtering and scenario-based Markov chains to predict the execution. Experimental validation on medical image processing shows an accuracy of 97%. As a result, the latency variation within non-deterministic analysis applications is reduced by 70% by adaptively splitting/merging of tasks. Furthermore, the parallel execution of a deterministic live-viewing application features constant throughput and latency by dynamically switching between quality modes. Interestingly, our solution can successfully be ...

• Type: Conference
• Year: 2009
• Where: ICIP
• Keywords: Heterogeneous Medical Imaging, ICIP 2009, Image Processing