Energy-aware scheduling of bag-of-tasks 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 superlinear power consumption laws, we investigate different models, with energy overheads and memory constraints. Building upon closed-form expressions for the uni-processor case, we derive asymptotically optimal solutions for all models.