  Regional data center clusters have flourished in recent years to serve
customers in a major city with low latency. The optimal coordination of data
centers in a regional cluster has become a pressing issue because of its rising
energy consumption. In this paper, a Lyapunov optimization-based online
algorithm is developed for the combined computing workload and energy
coordination of data centers in a regional cluster. The proposed online
algorithm is prediction-free and easy to implement. We prove that the workload
queues and battery energy level will be within their physical limits, though
their related time-coupling constraints are not considered explicitly in the
proposed algorithm. The previous online algorithms do not have such a
guarantee. A theoretical upper bound on the optimality gap between the online
and offline results is derived to provide a performance guarantee for the
proposed algorithm. To enable distributed implementation, an accelerated ADMM
algorithm is developed with iteration truncation and follow-up well-designed
adjustments, whereby a nearly optimal solution is attained with much enhanced
computational efficiency. Case studies show the effectiveness of the proposed
method and its advantages over the existing methods.
