Facebook users share over 25 billion pieces of content, and view 500 billion pages, every month. (One of Facebook’s clusters has over 2250 machines and 23,000 cores, compressing 80-90 TB of data every day). Similarly, Linkedin crunches over 120 billion relationships per day. Do you ever wonder how much the electricity is costing?
The largest internet companies operate hundreds of thousands of servers that consume many megawatts of electricity, as much as tens of thousands of US homes. The numbers are staggering, and growing fast. (A recent report from Greenpeace entitled “How dirty is your data” ranks big data companies by energy source.)
Organizations such as Facebook, Linkedin, Google, Microsoft, Amazon, Yahoo and Rackspace cannot ignore their energy costs. One estimate of annual electricity costs of some of the larger players is below:
Electricity prices can vary significantly between two different locations, due to demand differences, transmission efficiencies and generation diversity. Is there any way to exploit temporal and geographic fluctuations in electricity pricing for economic benefit?
Consider the following electricity pricing variation table (for illustrative purposes only, based on 2009 next-day data):
Some real arbitrage possibilities exist for a pricing-intelligent routing algorithm. One study suggests that we can reduce energy cost by up to 30 percent, without a significant difference in client-server distances. We encourage use of our comprehensive tariff database to achieve these economic and environmental efficiencies.