In this paper, we design an analytically and experimentally better online energy and job scheduling algorithm with the objective of maximizing net profit for a service provider in green data centers. We first study the previously known algorithms and conclude that these online algorithms have provable poor performance against 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 various settings. 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 implemented as an empirical benchmark.
@article{arxiv.1404.4865,
title = {On Time-Sensitive Revenue Management and Energy Scheduling in Green Data Centers},
author = {Huangxin Wang and Jean X. Zhang and Fei Li},
journal= {arXiv preprint arXiv:1404.4865},
year = {2014}
}