Data centers are critical, energy-hungry infrastructures that run large-scale Internet-based
services. Energy consumption models are pivotal in designing and optimizing energy …

Smart grid has modernized the way electricity is generated, transported, distributed, and
consumed by integrating advanced sensing, communications, and control in the day-to-day …

Marginal-cost-based dynamic pricing of electricity services, including real power, reactive
power, and reserves, may provide unprecedented efficiencies and system synergies that are …

Efficient resource provision which can guarantee the satisfactory cloud computing services
to the end user, lays the foundation for the success of commercial competition. In the Iaas …

This paper surveys the opportunities and challenges in an emerging area of research that
has the potential to significantly ease the incorporation of renewable energy into the grid as …

We study the demand response (DR) of geo-distributed data centers (DCs) using smart
grid's pricing signals set by local electric utilities. The geo-distributed DCs are suitable …

In order to reduce the energy cost of data centers, recent studies suggest distributing
computation workload among multiple geographically dispersed data centers by exploiting …

We study\emph {smoothed online convex optimization}, a version of online convex
optimization where the learner incurs a penalty for changing her actions between rounds …

We consider online convex optimization (OCO) problems with switching costs and noisy
predictions. While the design of online algorithms for OCO problems has received …

Making use of predictions is a crucial, but under-explored, area of online algorithms. This
paper studies a class of online optimization problems where we have external noisy …