Data centers are an increasingly significant source of energy consumption. A recent EPA report to Congress estimated that U.S. servers and data centers used about 61 billion kilowatt-hours of electricity in 2006, or 1.5 percent of the total electricity used in the country that year. (See also “Data Centers’ Growing Power Demands.”) Concern about the amount of energy eaten up by data centers has led to a slew of research in the area, including new work from Microsoft Research’s Networked Embedded Computing group, which was showcased last week in Redmond, WA, at Microsoft’s TechFest 2008. The work attacks the energy-consumption problem in two ways: new algorithms make it possible to free up servers and put them into sleep mode, and sensors identify which servers would be best to shut down based on the environmental conditions in different parts of the server room. By eliminating hot spots and minimizing the number of active servers, Microsoft researchers say that the system could produce as much as 30 percent in energy savings in data centers.
The sensors, says Feng Zhao, principal researcher and manager of the group, are sensitive to both heat and humidity. They’re Web-enabled and can be networked and made compatible with Web services. Zhao says that he envisions the sensors, which are still in prototype form, as “a new kind of scientific instrument” that could be used in a variety of projects. In a data center, the idiosyncrasies of a building and individual servers can have a big effect on how the cooling system functions, and therefore on energy consumption. Cooling, Zhao notes, accounts for about half the energy used in data centers. (He believes that the sensors, which he says could sell for $5 to $10 apiece, could be used in homes as well as in data centers, where they could work in tandem with a Web-based energy-savings application.)
Another aspect of the research, explains Lin Xiao, a researcher with the group, is new algorithms designed to manage loads on the servers in a more energy-efficient way. Traditionally, load-balancing algorithms are used to keep traffic evenly distributed over a set of servers. The Microsoft system, in contrast, distributes the load to free up servers during off-peak times so that those servers can be put into sleep mode. The algorithms are currently designed for connection servers, which are employed with services for which users may log in for sessions of several hours, such as IM services or massively multiplayer online games. Because long sessions are common, shifting loads requires complex planning in order to avoid disconnecting users and other problems with quality of service. Xiao says that the group has developed two types of algorithms: load-forecasting algorithms, which predict a few hours ahead of time how many servers will need to be working, and load-skewing algorithms, which distribute traffic according to the predictions and power down relatively empty servers.
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