Online Electricity Cost Saving Algorithms for Co-Location Data Centers

This work studies the online electricity cost minimization problem at a co-location data center, which serves multiple tenants who rent the physical infrastructure within the data center to run their respective cloud computing services. The co-location operator has no direct control over power consumption of its tenants, and an efficient mechanism is desired for eliciting desirable consumption patterns from the tenants. Electricity billing faced by a data center is nowadays based on both the total volume consumed and the peak consumption rate. This leads to an interesting new combinatorial optimization structure on the electricity cost optimization problem, which also exhibits an online nature due to the definition of peak consumption. We model and solve the problem through two approaches: the pricing approach and the auction approach, and design online algorithms with small competitive ratios.