Task allocation for decoding multiple hard real-time video streams on homogeneous NoCs

Hard-real time video systems require deterministic admission control decisions to maintain high levels of predictability. These decisions can be based on the state-of-the-art schedulability analysis of tasks and flows. However, due to the pessimistic behaviour of the schedulability analysis and the uncertainties in the application, the multi-core system resources are usually under-utilised. In this paper we propose two task allocation techniques that exploit application and platform characteristics in order to increase the number of simultaneous, fully schedulable, video streams handled by the system. The first, more generic technique, uses the worst-case remaining slack of the mapped tasks as a heuristic to determine the task to processing core allocation. The paper also investigates a second technique that maps the heavily communicating, critical path tasks of the applications onto same core to reduce the communication overhead. We compare against other heuristic based dynamic mapping techniques in the literature, and show that an overall improvement of up to 10%-15% can be obtained, in admission rates and system utilisation.