On the energy optimization for precedence constrained applications using local search algorithms

We investigate the problem of scheduling precedence constrained applications on a distributed heterogeneous computing system with the aim of minimizing schedule length and reducing energy consumption. We present a scheduling algorithm based on the best-effort idea that promotes local search algorithms and dynamic voltage scaling to reduce energy consumption. The final goal is to maintain a given performance while minimizing energy use. The proposed approach first uses a list-based scheduling algorithm to find near-optimal solutions for schedule length, then local search algorithms with dynamic voltage scaling are applied to reduce energy consumption. However the algorithm it´s not allowed to deteriorate the schedule length computed by the best-effort algorithm. We discuss simulation results obtained with sets of real-world applications that emphasize the interest of the approach.