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 resource-usage 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 reused for alternative applications with several parallel streams, like in surveillance.
|Title of host publication||Proceedings of the 16th IEEE International Conference on Image Processing, ICIP, 7-10 November, 2009, Cairo, Egypt|
|Place of Publication||Piscataway|
|Publisher||Institute of Electrical and Electronics Engineers|
|Publication status||Published - 2009|