  Green data centers have become more and more popular recently due to their
sustainability. The resource management module within a green data center,
which is in charge of dispatching jobs and scheduling energy, becomes
especially critical as it directly affects a center's profit and
sustainability. The thrust of managing a green data center's machine and energy
resources lies at the uncertainty of incoming job requests and future
showing-up green energy supplies. Thus, the decision of scheduling resources
has to be made in an online manner. Some heuristic deterministic online
algorithms have been proposed in recent literature. In this paper, we consider
online algorithms for green data centers and introduce a randomized solution
with the objective of maximizing net profit. Competitive analysis is employed
to measure online algorithms' theoretical performance. Our algorithm is
theoretical-sound and it outperforms the previously known deterministic
algorithms in many settings using real traces. To complement our study, optimal
offline algorithms are also designed.
