Energy-Aware Scheduling of Flow Applications on Master-Worker Platforms

We consider the problem of scheduling an application composed of independent tasks on a fully heterogeneous master-worker platform with communication costs. We introduce a bi-criteria approach aiming at maximizing the throughput of the application while minimizing the energy consumed by participating resources. Assuming arbitrary super-linear power consumption laws, we investigate different models for energy consumption, with and without start-tip overheads. Building upon closed-form expressions for the uniprocessor case; we derive optimal or asymptotically optimal solutions for both models.