ACM e-Energy 2016 Session 2 (June 22)

Talk 1: Leveraging Energy Storage to Optimize Data Center Electricity Cost in Emerging Power Markets (

Yuanyuan Shi made the presentation for this paper. She introduced how to utilize battery storage for participating in the regulation services to reduce the electricity bill. The regulation service is an interaction between the data center and the grid. The cost saving consists of reducing the peak demand charge and gaining revenue from participating in regulation markets. In the trace-driven experiments, the electricity bill can be significantly reduced by the battery-based approach.


Talk 2: How to Cool Internet-Scale Distributed Networks on the Cheap (

Stephen Lee made the presentation for this paper. He introduced how to utilize the open air cooling and the load-balancing managing in Internet-scale Distributed Network (IDN) for decreasing the total cooling cost in the data center. The cooling cost can be reduced by transporting some workloads among multiple geo-distributed data centers, and thus the joint new techniques can reduce the total cost (i.e., transfer cost and cooling cost).


Talk 3: Joint Capacity Planning and Operational Management for Sustainable Data Centers and Demand Response (

Tan N. Le made the presentation for this paper. He introduced how to utilize the information predictions to find out a more efficient combination of the capacity planning expenses and operational management expenses in future multiple years. The capacity planning is about how the infrastructures develop in the future years, and the operational management is about the expense of workloads in the future years. Even though the prediction of one source might not be accurate, the framework can still obtain some comparable good results due to the variety of the energy sources.


This session mainly introduces three interesting topics in energy-efficient datacenters. The topics include electricity bill reduction by utilizing backup battery, cooling cost reduction by utilizing the open air cooling system, and data center building cost by utilizing the prediction of historical data.


Personally, I favorite talk 1 and especially love the trace-driven experiments of electricity markets. It would be better if the future work could prove some theoretical performance bounds or handle the more general battery models.


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