Online data intensive systems such as web search engines perform distributed query processing on computer clusters composed by thousands of computers and hosted in large data centres. While data center facilities enable large-scale online services, they also raise economical and environmental concerns. Therefore, it is important to reduce the energy expenditure of data centers, as well as to reduce carbon dioxide emissions and the negative impact of the data centers on the environment.
A large part of the energy consumption of a data center could be accounted to inefficiencies in its cooling and power supply systems. However, search companies already adopt state-of-the art techniques to reduce the energy wastage of such systems, leaving little room for more improvements in those areas. Therefore, new approaches are necessary to mitigate the environmental impact and the energy expenditure of online data intensive systems.
Reducing the energy consumption of CPUs represents an attractive venue for online data intensive systems. Currently, CPU cores frequencies are typically managed by operating system components, called frequency governors. Since online data processing systems comply with service-level objectives expressed as time deadlines, we advise that online data intensive systems should not process data faster than user expectations and, consequently, it is possible to design scheduling algorithms that, while minimising the energy consumption, do not allow violations on the data processing deadlines.