On time-sensitive revenue management in green data centers

In this paper, we design an analytically and experimentally better online energy and job scheduling algorithm with the objective of maximizing net profit for service providers in green data centers. We first study the previously known algorithms and conclude that these online algorithms have provable poor performance in their worst-case scenarios. To guarantee an online algorithm's performance in hindsight, we design a randomized algorithm to schedule energy and jobs in the data centers and prove the algorithm's expected competitive ratio in a special setting. Our algorithm is theoretical-sound and it outperforms the previously known algorithms in many settings using both real traces and simulated data. An optimal offline algorithm is also provided as an empirical benchmark.