On the Performance of Greedy Algorithms for Power Consumption Minimization

We revisit the well-known greedy algorithm for scheduling independent jobs on parallel processors, with the objective of minimizing the power consumption. We assess the performance of the online version, as well as the performance of the offline version, which sorts the jobs by non-increasing size before execution. We derive new approximation factors, as well as examples that show that these factors cannot be improved, thereby completely characterizing the performance of the algorithms.