Energy and power costs are a big part of the decision process when it comes to locating data storage or a complete data center for a company. An MIT PHD student has just created an algorithm to help companies serve and store data based on energy prices.
An Internet-routing algorithm that tracks electricity price fluctuations could save data-hungry companies such as Google, Microsoft, and Amazon millions of dollars each year in electricity costs. A study from researchers at MIT, Carnegie Mellon University, and the networking company Akamai suggests that such Internet businesses could reduce their energy use by as much as 40 percent by rerouting data to locations where electricity prices are lowest on a particular day.
Modern datacenters gobble up huge amounts of electricity and usage is increasing at a rapid pace. Energy consumption has accelerated as applications move from desktop computers to the Internet and as information gets transferred from ordinary computers to distributed “cloud” computing services. For the world’s biggest information-technology firms, this means spending upwards of $30 million on electricity every year, by modest estimates.
Asfandyar Qureshi, a PhD student at MIT, first outlined the idea of a smart routing algorithm that would track electricity prices to reduce costs in a paper presented in October 2008. This year, Qureshi and colleagues approached researchers at Akamai to obtain the real-world routing data needed to test the idea. Akamai’s distributed servers cache information on behalf of many large Web sites across the US and abroad, and process some 275 billion requests per day; while the company does not require many large datacenters itself, its traffic data provides a way to model the demand placed on large Internet companies.
As Cloud computing and Storage as a Service become ubiquitous, data centers will market themselves as low cost power providers, and high tech jobs will probably follow the equipment to locations that provide the lowest energy costs.
The Energy grid and the connectivity grid will probably begin to grow towards the lower cost providers as more organizations recognize the price advantages. As the grids mature the low cost areas will end up with a set of competitive advantages in connectivity and power over the current high cost power provider areas.
