A study of electricity price features on distributed internet data centers

Many modern cloud services are provided using Internet Data Centers (IDCs), e.g. the Google search engine. A network of IDCs is implemented using a set of data centers that are geographically distributed over many locations. The energy requirements of these systems are considerable, and there is growing interest in minimizing the total cost of energy required to operate them either by making the hardware more energy efficient or by ensuring that opportunities to access low-cost energy are exploited. In this paper we present a methodology for studying the energy cost implications of minimizing IDC energy costs under different operational and energy cost prediction regimes. We systematically study the impact of the level of price variability, time lag between locations due to the geographical distribution, reconfiguration delay, and accuracy of price predictions, on the overall electricity cost associated with managing an IDC.