A Power-Aware Online Scheduling Algorithm for Streaming Applications in Embedded MPSoC

As application complexity grows, embedded systems move to multiprocessor architectures to cope with the computation needs. The issue for multiprocessor architectures is to optimize the processing resources usage and power consumption to reach a higher energy efficiency. These optimizations are handled by scheduling techniques. To tackle this issue we propose a global online scheduling algorithm for streaming applications. It takes into account data dependencies between pipeline tasks to optimize processor usage and reduce power consumption through the use of DPM and DVFS modes. An implementation of the algorithm on a virtual platform, executing a WCDMA application, demonstrates up to 45% power consumption gain while guaranteeing regular data throughput.